Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades. It is currently unknown how climate and land use changes could affect the endemic area of Lassa virus, a zoonotic pathogen responsible for Lassa fever. Here, the authors show that by 2070, new regions in Africa will likely become ecologically suitable for Lassa virus, drastically increasing the population living in conditions favourable for virus circulation. Lassa is a viral hemorrhagic fever with variable but generally high case fatality rates6 for which efficacious countermeasures are lacking8. There is currently no vaccine approved to prevent Lassa. Although several candidates have shown promising results during preclinical studies, only one (INO-4500) has progressed to clinical trials 10. Regarding Lassa treatment, the only antiviral drug available is the nucleoside analog ribavirin11, which is often ineffective7. To date, Lassa cases have mostly been reported in West Africa including Guinea, Liberia, Nigeria, and Sierra Leone. While these countries seem to constitute most endemic hotspots12, local under-reporting could potentially bias this overall picture. Nigeria, in particular, has witnessed a significant increase in incidence in recent years, and confirmed more than a thousand cases in 202013. Increasingly, neighbouring countries, including Benin, Ghana, Ivory Coast, Mali, and Togo, have also been reporting infections17, suggesting that the true Lassa range may span a sizable part of West Africa.Along with other viral infections that have gained prominence in recent years18, a member of the Arenaviridae family (genus Mammarenavirus). Human infections are generally thought to occur through direct contact or exposure to the excreta of infected Mastomys natalensis23, although the main transmission mechanism remains to be formally established. M. natalensis rodents often live in close contact with human communities24 and are regarded as the primary reservoir for the virus25. Humans likely contribute little to virus transmission and are considered dead-end hosts, based on studies of rodent biology18, ecology28, transmission dynamics29, and viral genomes32. While the virus can only spread where its reservoir is present, the range of M. natalensis extends beyond that of Lassa virus, spanning most of sub-Saharan Africa34. The factors underlying this difference in range between the virus and its reservoir have led to long-standing questions about suitability and may be multifactorial: Lassa virus might exclusively circulate within one of the six M. natalensis phylogroups or subspecies, namely A-I35, which is only found in West Africa37; other viruses present in M. natalensis populations may prevent Lassa virus circulation through competition39; closely related mammarenaviruses inducing cross-reactive immunity42 may prevent Lassa virus infection; and finally, Lassa virus prevalence may be influenced by different environmental determinants than its reservoir, as in the case of Sin Nombre virus43. For this other rodent-borne virus, environmental conditions can impact the abundance of the host, driving the population density of the reservoir below the threshold needed for virus maintenance45.Lassa is caused by Lassa virus49. Additional biological and socio-ecological factors may further influence spill-over dynamics, as suggested by mechanistic modelling investigations50. Most of these studies have mapped the current risk for Lassa virus infection in West Africa, identifying risk areas across much of this region49. Like the rest of the world, African countries will increasingly be affected by climate change, with warming temperatures and more extreme, yet rarer, precipitation53. These changes, combined with an increasing pressure on land resources due to a considerable projected human population expansion, are expected to result in important transformations of land use throughout Africa56. Previously, Redding and colleagues showed that spill-over events would at least double by 2070 within the Lassa-endemic western African region due to climate change, human population growth, and to a smaller extent, land use changes46. It is not known, however, how these environmental changes may affect the distribution of the virus itself57.Ecological niche modelling studies have identified—although not always agreed on — environmental factors that correlate with the occurrence of Lassa virus infections in rodent and human hostsIn this work, we add to previous modelling studies by combining ecological niche modelling and phylogeographic analyses to investigate how the endemic range of Lassa virus may evolve in the next five decades in response to climate change, human population growth, and land use changes. We start with using ecological niche modelling to assess whether regions outside the current endemic range may become suitable for Lassa virus due to changes in environmental conditions. To identify factors driving suitability for virus circulation, we analyse the environmental data associated with the occurrence of Lassa virus for a set of putative explanatory factors. We find that annual mean temperature, annual precipitation, and the presence of pastures are the main factors determining ecological suitability for Lassa virus circulation. Using projections of climate, land use, and population up to 2070, we estimate future ecological suitability and show that within decades, the range suitable for Lassa virus may extend well beyond West Africa. Using population projections, we then estimate that the extended part of the suitable range will be home to an increasingly large number of people in the next decades. We hypothesise that if Lassa virus is introduced into a new suitable region, it could in theory spread there because its reservoir host is present. This process, however, might take time. To gain insights into how fast the virus may be able to spread through a suitable environment, we subsequentely perform spatially-explicit phylogeographic analyses. Using geotagged viral genomes, we show that over the first decades following a successful introduction into a new region its propagation could remain spatially limited, unless the virus spreads significantly faster than in current endemic areas. By combining ecological niche modelling with spatially-explicit phylogeography, our study showcases how climate and land use change may transform the future risk of Lassa in Africa.M. natalensis, we built ecological niche models, considering temperature, precipitation, seven types of land cover, and human population as potential determinants. Using a boosted regression trees58 (BRT) method, we searched for associations between known occurrences of the virus and its reservoir and the environmental conditions at those sites. As inputs for our models, we used occurrence records collated from online databases and the literature and environmental data obtained from the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b)59. To assess how each factor contributed to our models, we calculated their relative importance (RI). In the case of BRT models, RI is evaluated based on the number of times the factor is selected for splitting a tree, weighted by the squared improvement to the model as a result of each split, averaged over all trees59.To identify factors that determine ecological suitability for Lassa virus and M. natalensis, we found that precipitation was the main contributor , precipitation (RI = 24.5%), pastures and rangeland coverage  and 1 (highly suitable conditions). We found that temperatures below 25 °C or values of pastures and rangeland coverage below 20% seem unsuitable for the virus  according to three climate scenarios: representative concentration pathways (RCPs) 2.6, 6.0, and 8.5 — which describe the evolution of global warming depending on different trajectories of greenhouse gases atmospheric concentrations61. For the present-day situation, our ecological niche maps for Lassa virus and M. natalensis were in agreement with previous estimates48, showing Lassa virus suitability across West Africa, predominantly in current endemic countries of Guinea, Sierra Leone, Liberia, and Nigeria  for Lassa virus  driving the expansion of the niche of Lassa virus, we represented, on a map of Africa, the environmental values for the main factors influencing ecological suitability at current and future time points Figs. , S5. In M. natalensis is (and will remain) present, as indicated by our estimates of present and future suitability for M. natalensis across Africa  and found that they are currently home to 179 million people [159–199]. This result suggests that the population is expected to grow substantially throughout the entire niche of the virus (as projected in 2070), which will more than triple by 2070  and a small (S) segment that may reassort during coinfections in M. natalensis64. As reassortment may result in distinct evolutionary histories for the L and S segments, we analysed them in separate phylogeographic inferences . We also divided our analyses between four main clades , we estimated the weighted lineage dispersal velocity33.To determine how slow the velocity of Lassa virus circulation was compared to other zoonotic viruses, we assembled and sorted all published estimates of weighted lineage dispersal velocities Table . We founM. natalensis for transmission, any environmental feature limiting the mobility of the reservoir may also impact virus dispersal. Main waterways in particular, have been proposed to act as barriers preventing the spread of Lassa virus, based on phylogenetic evidence that virus diversity is distinct across different sides of the Niger and Benue rivers in Nigeria66  — a proxy for river stream size, based on a hierarchy of tributaries71. We found only moderate evidence (3 <BFs <20)72 that the virus dispersal trajectory tends to avoid crossing rivers, no matter the Strahler number used as cut-off value for the stream size , due to the coarse scale of climate change projections75. This limited resolution reduced our ability to account for small-scale environmental variations that could affect suitability for Lassa virus; however, the good performance of our models (area under the receiver operating characteristic curves between 0.74 and 0.85) suggests that our approach provides a reasonable estimate of the distribution of Lassa virus infections.M. natalensis subtaxon A-I37. Records of Lassa virus infection in M. natalensis subtaxon A-II76 and in other rodent species including M. erythroleucus or Hylomyscus pamfi77 suggest, however, that susceptibility to Lassa virus infection may not be species or subtaxon specific. Other possible explanatory factors include intra-host competition between different viruses78, or cross-immunity due to the circulation of closely related viruses41. As most other old world arenaviruses that circulate in M. natalensis are found only in East Africa37, there is little data to assess these two mechanisms based on field data. Only in Mayo-Ranewo , rodent trapping studies have identified a Mobala-like virus in M. natalensis79, which does not seem to effectively restrict the transmission of Lassa virus, as human infections are often reported in that state of Nigeria80.In addition to environmental aspects, several other factors may also contribute to the difference in distribution between Lassa virus and its reservoir. As reported for other mammarenaviruses, the virus may only be present in the M. natalensis rodents travel rarely outside of their commensal habitat and are prone to high levels of consanguinity33. However, it is surprising that Lassa virus ― and by implication its reservoir ― seem unrestricted by the environment. Of note, our results were not always consistent between the L and S segments, possibly due to the lower number of L sequences (255) in our data set compared to S sequences (411). More generally, the number of genomic sequences in our datasets may offer limited power for the tests we used to assess the possible impact of rivers and other environmental factors on virus spread. Hence, a larger sampling of Lassa virus genomes throughout the virus range would allow for better evaluation of the role of the environment in limiting spread. Another caveat here is that our procedure considers constant-in-time environmental values that do not reflect changes in climatic and land cover conditions that may have occurred throughout the virus dispersal history. Indeed, it is estimated that in the past century alone, about 10 million ha of forest were lost in West Africa, mostly to the benefit of agricultural expansion81. Over the same period, annual precipitation has decreased throughout the area while temperatures have risen, up to over 1 °C in some parts of Nigeria82. To address this issue, we restricted our analysis to the most recent dispersal events in the virus dispersal history which date back, on average, to the 1990s. However, our approach still does not account for abrupt changes in climate, land use, and population density that may have occurred throughout the last decades in the West African region56.In our phylogeographic analyses we find that Lassa virus mostly spreads on a small spatial scale, with relatively few long-distance dispersal events Fig.  but we dIn our study, we use phylogeographic simulations to highlight how, in the absence of restrictions from the environment, a slow lineage dispersal velocity may limit the propagation of Lassa virus in case of a successful introduction into a new ecologically suitable area. We use these simulations for illustration and not prediction as the dispersal dynamics upon virus emergence in a new region are unclear. The virus may spread swiftly through an immunologically naïve rodent population, but the low mobility of the rodent reservoir could still limit the velocity of virus dispersal on a larger scale. As underlined above, a number of other elements may also come into play, such as the nature of host species or subtaxa as well as potential cross-immunity or competition due to the local co-circulation of closely related viruses. Nevertheless, it is worth pointing out that following the emergence of Lassa virus in the MRU, virus circulation remained as slow — if not slower — as in Nigeria, as highlighted by our estimates of weighted lineage dispersal velocity Fig. .32. This early part of the virus dispersal history, however, remains poorly understood and it is thus hard to predict if the virus is likely to travel across the African continent again. In addition, some factors may hinder virus dispersal following a hypothetical introduction into a new ecologically suitable region. First, in our analyses, as there is evidence that Lassa virus infection may not be species or subtaxon-specific77, we considered the entire M. natalensis species to be susceptible to Lassa virus infection. It is, however, possible that the virus spreads less (or more) efficiently in a different subtaxon of M. natalensis. Second, while in most of the areas where ecological suitability for LASV appears to increase over time outside of West Africa , no Mammarenavirus species have so far been identified12, we cannot rule out the possibility that potential cross-immunity or competition due to the local co-circulation of closely related viruses may hinder the propagation of LASV.Our ecological niche modelling analyses highlight a risk of expansion of Lassa virus towards regions in Central and East Africa that could potentially lead to a drastic increase in the number of people living in areas ecologically suitable for Lassa virus Table . To reacTo provide a very conservative estimate of the future risk of exposure to Lassa virus, we can focus on population growth in the endemic range and leave aside its possible expansion. When considering a cut-off value of 0.5 for the ecological suitability threshold defining the niche of the virus, we estimated that population growth in endemic countries could alone put 186  and 341 [315–369] million people at risk of infection by 2030 and 2070, respectively Table , compare86. These measures will, however, remain crucial to prevent infections. Even more so as we report an extremely slow dispersal velocity of Lassa virus in endemic areas, suggesting that localised efforts that target infection hotspots may prove to be highly effective.In this analysis, we focused on evaluating the population that will likely be exposed to Lassa in endemic regions or that might be exposed in regions that we predict to be suitable for Lassa virus in the future. Importantly, we did not evaluate how much heightened surveillance, improved sanitation, and increased awareness may help to reduce exposure to Lassa virus in the future87. This uptick was not attributed to increased inter-human transmission31 or to the emergence of a specific viral strain31; but raised the question of a more intense circulation within the reservoir or of an improvement in surveillance and public awareness. To discriminate between these two hypotheses, we investigated the evolution of the overall genetic diversity of Lassa virus in the main Nigerian clade (clade II) over the past decades, using a coalescent approach that accounts for preferential sampling. We found that the effective population size of Nigeria clade II increased over the last years , a country that has reported an unusual increase in the number of reported Lassa fever cases over the last two years89. We showed that changes in temperature, precipitation, and pastures/rangeland land coverage may expand the ecological niche of Lassa virus beyond current endemic areas, potentially exposing hundreds of million more people to Lassa. By simulating virus spread, we highlight that, in the scenario of a successful introduction and propagation of the virus in a new ecologically suitable area, the emerging circulation foci could remain limited to a small spatial scale over the first decades. Our study provides an example of how ecological niche modelling and spatially-explicit phylogeography can be effectively combined to investigate the future risk of a major zoonotic disease.With anthropogenic climate change and an increasing impact of human activities on the environment, extensive studies of the ecology and spread of zoonotic and vector-borne diseases are needed to anticipate possible future changes in their distribution90 (BRT) approach implemented in the R package dismo58 (version 1.3-8) to perform ecological niche modelling analyses of both Lassa virus and its host, M. natalensis. BRT is a machine learning method that allows to model complex non-linear relationships between the probability of occurrence and various predictor variables91. This approach aims to generate a collection of sequentially fitted regression trees that optimise the predictive probability of occurrence based on predictor values91, which can also be interpreted as a measure of ecological suitability. In a comprehensive review of distribution modelling methods, Elith et al.90 found BRT to perform best along with the maximum entropy method92.We employed the boosted regression treesM. natalensis has been recorded. While heterogeneous disease surveillance efforts likely bias the spatial distribution of Lassa records47, this procedure avoids treating under-sampled areas as ecologically unsuitable for the virus, but also limits the potential impact of such heterogeneity in sampling effort or surveillance95. Of note, while several rodent species such as M. erythroleucus77 may be important for Lassa virus transmission, we chose to be conservative and focused on the main species recognised as a reservoir host for Lassa virus to define our background. Similarly, for M. natalensis, we only sampled pseudo-absences in raster cells in which the presence of at least one individual of another species belonging to the Muridae family has been recorded. Because it only requires a single occurrence record to consider a presence, we discarded all but one occurrence record per raster cell. We applied the same filtering step for the pseudo-absence points and simply discarded pseudo-absences falling in raster cells with occurrence data. This filtering procedure is required to only have a presence or a pseudo-absence assigned to each grid cell, but also has the advantage of minimising the risk of artefacts due to spatially heterogeneous disease/wildlife surveillance efforts in the resulting BRT models. Indeed, even in areas where the disease surveillance was limited, it only necessitates at least a single occurrence record to consider the presence of the target species in the large grid cell we use.The BRT approach requires both presence and absence data. When unavailable, as this is the case for Lassa virus and its host, absence data can be approximated by random pseudo-absence points sampled from the study area . For Lassa virus, we only sampled pseudo-absences in raster cells in which the presence of 95 (version 2.1.4). We employed a spatial rather than a standard cross-validation because the latter may overestimate the ability of the model to make reliable predictions when occurrence data are spatially auto-correlated97, which can frequently be the case. All BRT analyses were run and averaged over 10 cross-validated replicates, with a tree complexity set at 5, an initial number of trees set at 100, a learning rate of 0.005, and a step size of 10. We evaluated the inferences using the area under the receiver operating characteristic (ROC) curve, also simply referred to as “area under the curve” (AUC). Among replicates, AUC values ranged from 0.68 to 0.73 for M. natalensis (mean = 0.71), and from 0.74 to 0.85 for Lassa virus (mean = 0.79).To select the optimal number of trees in the BRT models, we used a spatial cross-validation procedure based on five spatially separated folds generated with the blockCV R packageM. natalensis species from the Global Biodiversity Information Facility , the Integrated Digitized Biocollections , the Field Museum of Natural History Zoological collections , and the African Mammalia database . This data set was supplemented with the data available in the scientific literature . Duplicate records as well as records located in the ocean were excluded from the final data set, totalling 2504 unique M. natalensis occurrence records. For 26 of those records, the location was not provided as spatial coordinates but as a locality (below or at the administrative level 4). Therefore, the latitude and longitude data correspond to that of the locality . Occurrence data for the Muridae family were obtained from the GBIF database . Duplicate records and records located in the ocean were excluded from the data set, totalling 10,806 unique Muridae occurrence records for the African continent. Occurrence data for Lassa virus were obtained by combining the data set from Fichet-Calvet & Rogers48 with records associated with sequences from our Lassa virus sequence data set , records of infected M. natalensis from our host occurrence data set and the data available in the scientific literature (search for term “Lassa virus” in PubMed). Duplicate records were discarded from the data set, resulting in 310 unique Lassa virus occurrence records. For two of those records, the location was not provided as spatial coordinates but as a locality (below or at the administrative level 4) so the latitude and longitude data corresponded to that of the locality . Our BRT models were trained on current environmental factors and then used to obtain estimates of future ecological niches for both Lassa virus and M. natalensis.We obtained occurrence data for 59. The climate information consists of daily gridded near-surface air temperature and surface precipitation fields derived from four bias-adjusted98 global climate models  participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5103). We considered simulations conducted under historical climate forcings and RCPs 2.6, 6.0, and 8.5. In addition, we considered observed gridded temperature and precipitation from the concatenated products GSWP3 and EWEMBI58 for assessing the current (1986-2005) conditions. For land cover, we used version 2 of the Land Use Harmonisation (LUH2104) providing historical and projected land cover states under a range of shared socioeconomic pathways (SSPs), and from which we considered SSP1-26, SSP4-6.0, and SSP8-85. Finally, we retrieved gridded population projections105 under SSP2-26. For each combination of product , scenario , and analysis window , we computed the grid-scale temporal mean. For each scenario and time period, we estimated an index of human exposure (IHE) which corresponds to human population estimates (log10-transformed) in raster cells associated with an ecological suitability for Lassa virus above or equal to 0.5. Specifically, we used these IHE values to calculate the number of people at risk of exposure to Lassa virus. To investigate the specific effect of human population growth in current and future suitable areas, we also re-estimated future IHE values using (i) current population estimates with future projections of ecological suitability for Lassa virus to estimate population growth throughout current and future suitable areas, and (ii) future projections of human population with current projection of ecological suitability for Lassa virus to estimate the future population living in current suitable areas n = 729 L and 1202 S sequences; database accessed on October 31, 2019). They were combined with recently generated sequences from Nigeria that have been sequenced using the MinION technology (Oxford Nanopore) in conjunction with a non-targeted metagenomic RNA sequencing approach31 and that are publicly available on the website virological.org . We filtered the data by: (i) excluding laboratory strains , (ii) excluding sequences without a timestamp, (iii) keeping only sequences from a single timepoint (if multiple timepoints were available for a patient), (iv) removing duplicates (when more than one sequence was available for a single strain), and (v) excluding sequences from identified hospital epidemics or sequences for which the location corresponded to the site of hospitalisation. The remaining sequences were trimmed to their coding regions and arranged in sense orientation separately for the S segment (NP-NNN-GPC) and the L segment (L-NNN-Z). The sequences were aligned using MAFFT106 (version 7) and inspected manually using the program AliView107 (version 1.26). At this step, we discarded low-quality sequences  and very short sequences (combined ORF length <500nt). Since there is an overlap between the sequence data from the work of Siddle and colleagues30 and of Kafetzopoulou and colleagues31, we excluded sequences with zero or one mismatch between the two sets of sequences to ensure that there would not be duplicates in our data sets. Two types of alignments were generated. The alignments with all curated sequences regardless of the availability of detailed location information included 756 S segment sequences and 551 L segment sequences, respectively. The alignments with detailed location information included 411 S segment sequences and 255 L segment sequences, respectively. For the sequences with detailed location information, when no spatial coordinates were provided but only a name, spatial coordinates were determined using a combination of online platforms , sampling Markov chain Monte-Carlo (MCMC) chains every 105 generations. We used Tracer 1.7110 for identifying the number of sampled trees to discard as burn-in, but also for inspecting the convergence and mixing, ensuring that estimated sampling size (ESS) values associated with estimated parameters were all >200. We used TreeAnnotator 1.1096 to obtain a maximum clade credibility (MCC) tree for each BEAST analysis. Finally, we used the R package seraphim67 to extract the spatiotemporal information embedded within trees obtained by spatially-explicit phylogeographic inference, as well as to estimate the weighted lineage dispersal velocity.We performed spatially-explicit phylogeographic reconstructions using the relaxed random walk (RRW) diffusion model70 to compute the total cost for viral lineages to travel through a landscape crossed by rivers. This algorithm uses an underlying environmental raster to compute the minimum cost to move from one position to another. Here, we generated rasters by assigning a value of 1 to raster cells that were not crossed by a main river and a value of 1 + k to raster cells crossed by a main river (raster resolution: ~0.5 arcmin). Because the raster cells that were not crossed by a main river were assigned a uniform value of 1, k thus defines the additional resistance to movement when the cell does contain such a potential landscape barrier112. In order to assess the impact of that rescaling parameter, we tested three different values for k: 10, 100, and 1000. Furthermore, as the notion of main river is arbitrary, we used different threshold values of the Strahler number S associated with each river to select the main rivers to consider in each analysis. In hydrology, S can be used as a proxy for stream size by measuring the branching complexity, i.e., the position of a river within the hierarchical river network. In practice, we compared the total cost computed for posterior trees with the total cost computed on the same trees along which we simulated a stochastic diffusion process under a null dispersal model113. Hereafter referred to as “simulated trees”, these trees were obtained by simulating a relaxed random walk process along the branches of trees sampled from the posterior distribution obtained by spatially-explicit phylogeographic inference113. Because this stochastic diffusion process did not take the position of rivers into account, we can expect the total cost to be lower for inferred trees under the assumption that viral lineages did tend to avoid crossing rivers. For each inferred or simulated tree, we computed the total cost TC, i.e., the sum of the least-cost values computed for each phylogenetic branch considered separately. Each inferred TC value (TCinferred) was then compared to its corresponding simulated value (TCsimulated) by approximating a Bayes factor (BF) support as follows: BF = [pe/(1-pe)]/[0.5/(1-0.5)], where pe is the posterior probability that TCsimulated > TCinferred, i.e., the frequency at which TCsimulated > TCinferred in the samples from the posterior distribution. The prior odds is 1 because we can assume an equal prior expectation for TCinferred and TCsimulated.Based on the spatially-explicit phylogeographic reconstructions, we performed two different kinds of analyses to investigate the impact of several environmental factors on the dispersal history and dynamics of Lassa virus lineages. First, we tested the impact of main rivers acting as potential barriers to Lassa virus dispersal , forest areas, grasslands, savannas, croplands, annual mean temperature, annual precipitation, and human population density. Except for the generated river rasters (see above), all these rasters had a resolution of ~2.5 arcmin. For one-dimensional landscape features such as rivers, we had to resort to higher resolution rasters (~0.5 arcmin) to obtain sufficiently precise pixelations (rasterizations) for this non-continuous environmental factor. Raster cells assigned to rivers would otherwise be exceptionally large given the size of the study area, which could potentially lead to artefactual results. Environmental rasters were tested as potential conductance factors  as well as potential resistance factors . For each environmental variable, we also generated several distinct rasters with the following formula: vt = 1 + k*(vo/vmax), where vt is the transformed cell value, vo the original cell value, and vmax the maximum cell value recorded in the raster. The rescaling parameter k here allows the definition and testing of different strengths of raster cell conductance or resistance, relative to the conductance/resistance of a cell with a minimum value set to 1114. For each of the three environmental factors, we again tested three different values for k . The following procedure can be summarised in three successive steps115: (i) based on environmental rasters, we computed environmental distance for each branch in inferred and simulated trees. These distances were computed using two different algorithms: the least-cost path and Circuitscape algorithm, the latter using circuit theory to accommodate uncertainty in the route taken116. For computational tractability, high resolution river rasters were only tested with the least-cost path algorithm. (ii) We estimated the correlation between time durations and environmental distances associated with each phylogenetic branch. Specifically, we estimated the statistic Q defined as the difference between the coefficient of determination obtained when branch durations are regressed against environmental distances computed on the environmental raster, and the coefficient of determination obtained when branch durations are regressed against environmental distances computed on a uniform “null” raster, i.e., a uniform raster with a value of “1” assigned to all its cells. We estimated Q for each tree and we thus obtained two distributions of Q values: one for inferred and one for simulated trees. We only considered an environmental raster as potentially explanatory if both its distribution of regression coefficients and its associated distribution of Q values were positive117. (iii) We evaluated the statistical support associated with a positive Q distribution  by comparing it with its corresponding null distribution of Q values based on simulated trees. We formalised this comparison by approximating a BF support as defined above, but this time defining pe as the posterior probability that Qestimated > Qsimulated, i.e., the frequency at which Qestimated > Qsimulated in the samples from the posterior distribution68. For computational reasons, the main rivers rasters, which had to be associated with higher resolution (see above), were only tested as resistance factors with the least-cost-path algorithm.Next, we tested the impact of several environmental variables, again described as rasters, on the dispersal velocity of Lassa virus lineages Table : main riWe implemented a phylogeographic approach to simulate virus dispersal over a 20-year period following a successful introduction event within a new ecologically suitable area in 2050 under scenarios RCP 6.0 and RCP 8.5. We simulated viral lineage dispersal events by randomly sampling from the dispersal events inferred by our phylogeographic analyses. These simulations were performed under the assumption of no notable impact of underlying environmental factors. To set the trajectory of lineage dispersal events, we selected the ending location with a probability defined by the local ecological suitability. The starting point of those simulations was selected arbitrarily within the most suitable area of the extended part of the ecological niche estimated for Lassa virus in 2050, and was thus different for simulations performed under scenarios RCP 6.0 and RCP 8.5.118 implemented in BEAST 1.1096. The skygrid model allows to estimate the past evolution of the viral population effective size through time. For these analyses, we also modelled the nucleotide substitution process according to a GTR + Γ parameterisation109 and branch-specific evolutionary rates according to a relaxed molecular clock with an underlying log-normal distribution110. In the case of NGA clade II for which we inferred a recent increase in the global effective population size, we also performed a preferential sampling analysis119. By modelling the sampling times as a process dependent on effective population size, this complementary analysis allows to explicitly take into account heterogeneous sampling density through time, which can improve estimates of global effective population size119.We performed demographic reconstructions using the flexible skygrid coalescent modelFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Results showed that the growth kinetics curve of rGS14-ΔCBP-ΔGIF and parental virus was consistent, both reaching plateau phase at 48 h post infection, which indicated that the double deletion of cbp and gif genes had little impact on the replication properties of the recombinant virus in primary goat testis (PGT) cell cultures compared with the parental virus. The safety of the double gene-deleted virus was evaluated in lambs. The lambs were monitored for 21 days post infection of the recombinant virus and no ORFV associated symptoms were observed in 21 days post-infection except for slight fever and anorexia in 5 days post-infection, and all lambs inoculated with either recombinant virus or PBS exhibited no clinical signs. To assess the protection efficacy of the rGS14-ΔCBP-ΔGIF, groups of four lambs each were inoculated with rGS14-ΔCBP-ΔGIF, rGS14-ΔCBP, rGS14-ΔGIF or PBS and challenged by a wild type virulent ORFV strain that was isolated from proliferative scabby lesions tissues of infected goat at 21-day post-inoculation. During 14 days post-challenging, lambs inoculated with rGS14-ΔCBP-ΔGIF all remained healthy with unimmunized group all infected, while the single gene-deleted viruses only protected 40% to 50% animals. These results indicated that the double gene-deleted recombinant virus could provide complete protection against virulent ORFV challenging. In conclusion, the double gene-deleted recombinant virus strain, rGS14-ΔCBP-ΔGIF, would be a promising candidate vaccine strains with safety, high protection efficacy and availability.Contagious ecthyma is a highly contagious viral disease with zoonotic significance caused by orf virus (ORFV) that affects domestic, ruminants and humans. Live attenuated virus and attenuated tissue culture vaccines are widely used in the fight against ORFV, however, the conventional attenuated vaccine strains have many drawbacks. The aim of this project was to construct a promising contagious ecthyma vaccine strain with safety, high protection efficacy and accessibility by genetic manipulation to against the disease. Using a natural ORFV-GS14 strain as the parental virus, recombinant virus, rGS14-ΔCBP-ΔGIF, with double deletions in the genes encoding the chemokine binding protein (CBP) and granulocyte/macrophage colony-stimulating factor inhibitory factor (GIF) was generated and characterized  Contagious ecthyma also known as orf, is a highly contagious and economically significant zoonotic viral skin disease in sheep and goats. It is characterized by proliferative skin and mucous membrane of the oral cavity, tongue, lips and ears which are developed sequentially in the form of papules, vesicles, pustules, scabs . GeneralParapoxvirus from Poxviridae, which has a linear double-stranded DNA genome of approximately 138 kbs encoding 132 genes  method to detect ORFV and used in phylogenetic analysis because of its specificity and conservation in ORFV  (ORFV117) (ORFV127) (ORFV112 that is located at the right end of the genome and is capable of disrupting chemokine gradients thereby inhibiting immune cells migrating to sites of infection (ORFV112 deletion resulted in the attenuation of ORFV NZ2 (Orf is caused by the epitheliotropic orf virus (ORFV), a member of the genus 32 genes –6. Many 32 genes –8. The g32 genes . The cen32 genes . The B2L in ORFV . F1L is nd goats . It is wORFV112) , granuloORFV117) , and intORFV127) –17 have nfection . It was ORFV NZ2 . GIF is ORFV NZ2 , 19. Thein-vivo assay, where inoculation with inactivated ORFV could not prevent re-infection of the host  ORFV recombinants based on a natural strain and then we investigated the effect of these deletions in ORFV replication and virulence in vitro and evaluated the safety and effectiveness by immune protection test in goats.The aim of this study is to construct a genetically stable attenuated ORFV mutant that can be used as a safer and efficient vaccine candidate strain by deleting genes presumably involved in ORFV immunomodulatory properties. We herein described the generation of two single-gene-deletion  of the wild virus suspension. The main virulence genes of this wild virus strain were identified by PCR and the primers used were shown in A strain of wild type ORFV obtained from goat infected with ORFV, was used to challenge the immunized animals. The crusted scab of diseased animal was collected and ground with 10 volumes (w/v) of PBS containing 10% antibiotics  followed by freeze-thaw cycles. And then the homogenate was centrifuged at 3,500 rpm for 10 min to collect the suspension, which was then filtered through 0.45 μm membrane. PCR method according to the previous study , 25 was For the targeted deletion of the CBP or GIF genomic locus by homologous recombination, two recombinant transfer vectors, comprising a selection marker gene, the upstream and downstream homologous arms flanking the target viral genomic region, were constructed by one-step fusion PCR method. Briefly, left (hm1) and right (hm2) arms flanking each target gene and corresponding selection GFP cassette were amplified by PCR, respectively. The GFP cassettes were amplified based on fragment of pEGFP-N1 and flanked on both sides with LoxP sites. The downstream of hm1 and the upstream of GFP cassette contain a section of complimentary sequence, the same with the downstream of GFP cassette and the upstream of hm2. Then the purified hm1, GFP cassette and hm2 were assembled to generate the recombinant transfer vectors by fusion PCR using primers of hm1 F and hm2 R, designated as pCBPhm1-GFP-CBPhm2 and pGIFhm1-GFP-GIFhm2. Primers used to construct the recombinant vectors were synthesized by Sangon Biotech (Shanghai) Co., Ltd, China Table 1.7.7 TCID50/mL of ORFV-GS14 and subsequently transfected with 4 μg of the transfer vector pCBPhm1-GFP-CBPhm2 and pGIFhm1-GFP-GIFhm2 separately at 24 h post-infection(pi), using 5 μL of Lipofectamine 3000 reagent  according to the manufacture. The plaques with a GFP signal were selected under fluorescence microscopy and further purified by limiting dilution assay. Genomic DNA was extracted using by AxyPrep body fluid viral DNA/RNA miniprep kit . PCR was performed to screen for the wild type virus contamination using internal primers including w-cbp F, w-cbp F, w-gif F and w-gif R . Plaques without GFP signal were picked to make virus stock and then passaged several times in PGT cells and purified further by limiting dilution. The excision of GFP from the viruses by Cre recombinase was confirmed by PCR of the GFP cassette using primers cbp-hm1 F, cpb-hm2 R and gif-hm1 F, gif-hm2 R, respectively.The reporter GIF gene was deleted from the cbp-deleted rGS14-ΔCBP as described above. For the deletion of gfp gene of the rGS14-ΔCBP-ΔGIF-GFP, a recombinant transfer vector without LoxP sites or reporter gene cassette containing left and right recombinant arms flanking the gif gene was constructed as described above. And the final double gene-deleted recombinant virus was generated by homologous recombination as described above and designed as rGS14-ΔCBP-ΔGIF. After successive purification, the genomic DNA of rGS14-ΔCBP-ΔGIF was extracted by AxyPrep body fluid viral DNA/RNA miniprep kit  and the deletion of both CBP and GIF genes were confirmed by PCR using the primers  per mL, which referred to previous study with slightly modification  followed by repeated freezing and thawing at -80°C. The thawed lysates were used to determine titers by TCID50 in PGT cells and virus load was qualified on each time point by using qPCR method.Replication properties of rGS14-ΔCBP-ΔGIF and parental ORFV-GS14 were assessed in PGT cell cultures. Preformed monolayers were prepared in 6-well plates and infected with the recombinant virus and parental virus at a MOI of 1, respectively. Then the cells were incubated at 37°C under 5% COcbp and gif gene deletion.To investigate the genetic stability of rGS14-ΔCBP-ΔGIF, serial passages of the virus were conducted in PGT cells. Low MOI (~1) infections were performed with the recombinant virus and cells were harvested at 48 h pi. Passages 1, 5, 10 and 15 viruses were subjected to PCR assays to evaluated the stability of the 6TCID50/mL in the labial commissures. Virus inoculation process referred to the method described previously , and inoculated with each of three ORFV-recombinants  or PBS. The lambs in the trial group were inoculated with 200 μL of a virus suspension containing 10eviously . The con5TCID50/mL) respectively and then were challenged with 100 TCID50 of orf virus on the 21st day post-inoculation.In challenge experiments, animals were inoculated with 200 μL of the three recombinant virus suspension .The main conservative gene and virulence genes of the parental ORFV-GS14 were identified by PCR, and agarose gel electrophoresis confirmed the existence of 50 of rGS14-ΔCBP-ΔGIF was 10-6.3/0.1 mL which was approximate to that of the parental ORFV-GS14 (10-6.7/0.1 mL). And the plaque size and morphology produced by the double gene deleted recombinant virus and parental virus at different time points post infection showed no significant differences .The stability of cbp and gif genes makes rGS14-ΔCBP-ΔGIF a safe candidate vaccine strain, lambs were inoculated with 200 μL of 106TCID50 rGS14-ΔCBP-ΔGIF following scarification of the oral commissures and monitored daily for 21 days. The virulence of rGS14-ΔCBP and rGS14-ΔGIF was also evaluated. All the inoculated lambs did not present any clinical sign associated with ORFV, and the cut healed on 5 to 7 days post-inoculation. No maculo-papular, ulcer and proliferative scabby lesions was observed in the skin of the lips, around the mouth or nostrils and oral mucosa during 21 days post-inoculation  by day 2 post-inoculation and then the temperature fell to and maintained the normal level from day 5 to 21 post-inoculation  or their precursors from the blood into the skin as well disrupting chemokine gradients that regulate the migration of activated DC to peripheral lymph nodes  when challenged at 21-day post-inoculation, while the single gene-deleted strains, rGS14-ΔCBP and rGS14-ΔGIF, protected only 40% (2/5) and 50% (2/4) of the animals respectively, with lambs in the control group all infected. The protective efficacy of the double gene-deleted strain was significantly better than that of the single-gene deletion strains. We suspected that the difference of the protection rate between rGS14-ΔCBP-ΔGIF and two single gene-deleted strains was caused by the effect of ph nodes . As a ceph nodes . The gifIn summary, in this study, we successfully generated a double gene-deleted ORFV, rGS14-ΔCBP-ΔGIF, by series homologous recombination method and evaluated its safety and protection potency in lambs. The results indicated that rGS14-ΔCBP-ΔGIF provided completely protection against wild virulent ORFV challenge and would be a promising candidate vaccine strains with safety and availability.The original contributions presented in the study are included in the article/This study was reviewed and approved by the Animal Care and Use Committee of China Institute of Veterinary Drug Control and China Institute of Veterinary Drug Control.in vitro. Cell culture and virus preparation. CY: animal experiments. XC: design the experiment and did the final approval of manuscript. All authors contributed to the article and approved the submitted version.ZZ: design the experiment and provided the techniques for the gene deletion. GQ, CW and ZYZ: literature review and interpretation, manuscript writing. JD, YC and ZS: Generate recombinant viruses and characterize the recombinant virus This work was supported by grant from the National Key Research and Development Program of China (No. 2016YFD0500906)The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


On the African continent, a large number of arthropod-borne viruses (arboviruses) with zoonotic potential have been described, and yet little is known of most of these pathogens, including their actual distribution or genetic diversity. In this study, we evaluated as a proof-of-concept the effectiveness of the nonspecific sequencing technique sequence-independent single primer amplification (SISPA) on third-generation sequencing techniques  by comparing the sequencing results from six different samples of arboviruses known to be circulating in Africa (Crimean–Congo hemorrhagic fever virus (CCHFV), Rift Valley fever virus (RVFV), Dugbe virus (DUGV), Nairobi sheep disease virus (NSDV), Middleburg virus (MIDV) and Wesselsbron virus (WSLV)). All sequenced samples were derived either from previous field studies or animal infection trials. Using this approach, we were able to generate complete genomes for all six viruses without the need for virus-specific whole-genome PCRs. Higher Cq values in diagnostic RT-qPCRs and the origin of the samples  along with their quality were found to be factors affecting the success of the sequencing run. The results of this study may stimulate the use of metagenomic sequencing approaches, contributing to a better understanding of the genetic diversity of neglected arboviruses. Recent pandemics have illustrated that emerging and re-emerging infectious diseases are of utmost importance for the global population. Despite not being a novel phenomenon, the worldwide transport of passengers and cargo, extensive land use, and the ongoing increase in the world population combined with urbanization and deforestation are favoring the emergence and accelerating the spread of pathogens . Most ofNGS plays an essential role in identifying novel genomes and analyzing epigenetic factors. Its innovation, effectively utilized and optimized over the past decade, has revolutionized the genomic investigation of humans as well as animals, plants and microorganisms ,6. Most However, one of the crucial steps usually required for NGS is the enrichment of the viral genomes in samples prior to sequencing. In this context, “sequence-independent single primer amplification” (SISPA), a method based on nonspecific amplification using random primers , represePhlebovirus), CCHFV, DUGV and NSDV (genus Orthonairovirus) belong to the order Bunyavirales and thus are RNA viruses characterized by a single-stranded tripartite genome. Their three genome segments are divided into a small (S-) segment of 1–2 kb, a medium (M-) segment of 3.7–5 kb, and a large (L-) segment varying from 6.8 to 12 kb [Alphavirus) and WSLV (genus Flavivirus) have an unsegmented, single-stranded RNA genome comprising approximately 11 kb [The main objective of the present study was to compare the number of specific sequencing reads of six selected arboviruses circulating in Africa using SISPA-based nanopore sequencing under different preconditions. Aside from Crimean–Congo hemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV), representing two very common and severe agents of zoonotic diseases in Africa, less well-studied pathogens such as Nairobi sheep disease virus (NSDV), Middelburg virus (MIDV), Dugbe virus (DUGV) and Wesselsbron virus (WSLV) were also sequenced as part of the study. Especially for the four last-mentioned viruses, scientific data are extremely limited , and theto 12 kb . In comply 11 kb ,21. In oThe results of this study may contribute to, as well as encourage, the generation and provision of viral sequences of neglected tropical arboviruses, allowing a better understanding of their genetic diversity and distribution.Six different viruses belonging to four different genera were analyzed by nanopore sequencing. For four of them, two different types of samples were tested and compared: samples of animal origin (vectors or hosts) from field studies or experimental animal trials and samples derived from cell culture. Moreover, for two selected viruses (CCHFV and RVFV), the obtained number of specific reads was compared for three different Cq values of the samples. ® VET kit  and a King Fisher extraction device  according to the manufacturer’s instructions. RNA extraction of in vitro samples was performed using the QIAamp Viral RNA Mini Kit . The extraction of RNA from samples of animal origin was conducted using the NucleoMagHyalomma ticks were collected from cattle and camels. The ticks were individually homogenized in AVL lysis buffer, and then RNA extraction was performed. For a better assessment of the influence of the Cq value on the quality of the sequencing output, three positive ticks with different Cq values  were selected for sequencing. The three field samples belonged to the lineages Africa I and III.The African strain Ibar10200 (Africa-I lineage) was grown on Vero E6 cells  under biosafety level (BSL)-4 conditions. Analysis of the extracted sample by RT-qPCR  revealedRattus rattus) that were infected with RVFV strain 35/74 under BSL-3 laboratory conditions [The live-attenuated RVFV vaccine strain MP-12 was grown on Vero 76 cells . After heat inactivation in AVL lysis buffer at 70 °C for 10 min, RNA extraction of the supernatant was performed. The following RT-qPCR  yielded nditions  was usedAmblyomma tick collected in 2018 in Nigeria [The Nigerian DUGV prototype strain IbAr 1792 , Galveston, TX, USA) was grown on SW13 cells , and RNA was extracted from the virus-containing supernatant. A Cq value of 15 was determined by RT-qPCR . The fie Nigeria . The ticThe NSDV strain IG619  was grown on SW13 cells. In RT-qPCR , the extThe MIDV strain MT MP160 and the WSLV strain SA H177  were grown on BHK-21 cells , and RNA extraction was performed from the virus-containing supernatants. By using RT-qPCR , Cq valuThe SISPA methodology was carried out using primers and PCR conditions as outlined in the protocol published by Peserico et al. . In the https://github.com/wdecoster/NanoPlot; accessed on 1 August 2022). Reads with a minimum quality of 7 were considered for further analysis. For consensus sequence generation from trimmed FastQ reads, alignment against redundant databases and mapping with reference genomes  were performed using k-mer alignment (KMA) [The steps of the data analysis are shown in Panel VI “Evaluation” of nt (KMA)  and Minint (KMA) . The KMAImportant quality parameters of the sequencing results  of all samples are summarized in The generated genome sequences are deposited in Genome assembly (de novo and map-to-reference) was successfully performed for samples with low Cq values , and ideIn recent years, third-generation sequencing with nanopores using MinION devices has become a reliable alternative and/or complement to second-generation sequencing techniques. Due to its small size and lower acquisitional costs, the device can be a valuable game changer, improving diagnostic capacities both in the field and in well-equipped laboratory facilities. Presequencing enrichment is a crucial aspect of sample preparation. In this context, virus-specific whole-genome PCRs are considered the gold standard, since due to their high specificity, whole-genome sequences can be obtained even with lower viral loads in the samples. However, more or less complex primer mixes have to be prepared depending on the virus to be sequenced. In some cases, very genetically diverse viruses such as CCHFV share only 70–80% of genetic identity among various strains , thus reA comparison of different samples of animal origin of CCHFV and RVFV showed that the highest number of specific reads was found in samples with lower Cq values, whereas the number of reads declined with increasing Cq values . In contThe quality of the reads and results obtained  generallIn general, the primer set of Peserico et al.  appearedIn this study, it has been shown that with good sample quality, the use of SISPA amplification and MinION sequencing can provide a nearly complete genome sequence of the virus in most cases. Regardless of read quality and coverage, very good identity levels (between 90–100%) were achieved for all viruses when comparing them with reference sequences in the public database. Even for the RVFV cell culture sample, excellent identity levels of 98.4–99.9% were obtained despite a comparatively low coverage of 11.29–24.97% B.In summary, this study demonstrates and underlines the broad applicability of enrichment with SISPA for MinION sequencing. As the method allows the generation of viral (full) genomes without the need for virus-specific whole-genome PCRs, the main application of SISPA consists in the sequencing of a broad range of pathogens previously detected by different PCR assays to obtain an initial overview of the genetic diversity inside the sample panel. This makes it particularly interesting for emerging or neglected viruses that do not have a large history of published whole-genome primer protocols  and also for laboratories that are less well equipped. Nevertheless, enrichment by virus-specific whole-genome PCR would result in a better sequencing result for samples with poorer quality or a higher Cq value. Additionally, SISPA could be used in more open sequencing approaches (metagenomics) to identify yet unknown infectious agents. However, the initial quality of the samples represents the main limiting factor for a successful sequencing run. If an initial screening of the sample in a virus-specific qRT-PCR is possible, the Cq value can be taken as a rough parameter.


Lactobacillus plantarum, Lactobacillus acidophilus, Bacillus subtilis or mixed lactic acid bacteria (L. plantarum and L. acidophilus with ration of 1:1)]. Structure, physicochemical, functional properties, and antioxidant activity of the wheat bran insoluble dietary fiber (W-IDF) modified by fermentation were studied. Fourier transformed infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM) analysis suggested the successful modification of W-IDF. After fermentation with L. plantarum and mixed lactic acid bacteria, the water retention capacity (WRC), oil retention capacity (ORC), and water swelling capacity (WSC) of W-IDF were improved. The sodium cholate adsorption capacity (SCAC), and cation exchange capacity (CEC) of W-IDF modified with L. acidophilus fermentation were significantly increased. Although the cholesterol adsorption capacity (CAC) of W-IDF decreased after modification with probiotic fermentation, nitrite ion adsorption capacity (NIAC), and total phenolic content (TPC) were enhanced. Additionally, W-IDF modified by fermentation with B. subtilis or mixed lactic acid bacteria exhibited superior antioxidant capacity verified by DPPH, ABTS and total reducing power assays. Results manifested that microbial fermentation is a promising methods to modify the W-IDF to provide high-quality functional IDF for food processing and human health management.Insoluble dietary fiber (IDF) were isolated from wheat bran (WB) after microbial fermentation with single or mixed strain [ In modern diet, daily intake of dietary fiber (DF) is inadequate for most people, due to the development of refined foods and excessive energy intake. Correspondingly, the incidence of sub-health and modern civilization diseases has been increased. Reasonable intake of DF is critical for health since it has been recognized as a beneficial nutrient to improve digestive tract health, lower blood lipids, regulate blood glucose, and control body weight. DF is generally divided into soluble dietary fiber (SDF) and insoluble dietary fiber (IDF). IDF displayed crucial role on human health via promoting intestinal peristalsis, improving bowel movements, protecting digestive system, reducing energy density, adsorbing and discharging grease and toxic substances such as heavy metals , 2. AddiIt was indicated that the various functional effects performed by IDF closely do with their different structures and components. Various methods have been applied to modify the structure or properties of IDF, such as physical, chemical, enzymatic or combined methods, and microbial fermentation. After modification, properties of IDF including hydration, adsorption, ion exchange activities were accordingly improved, which made IDF have a stronger ability to suppress the activity of enzymes including lipase and digestive enzymes –6. ThereBacillus natto not only enhanced the proportion of SDF, but also increased the adsorption capacity of IDF for cholesterol, bile salts, nitrite, as well as glucose. The content of total phenol and DPPH free radical scavenging ability were also visibly improved (ex vivo (Wheat bran (WB), a kind of main by-products of flour processing, consists of abundant IDF, yet its utilization efficiency is low because of the poor palatability and difficulty in digestion of wheat bran IDF (W-IDF) . Modificimproved . Ferment. Effects of biological modification on the structural, physicochemical, functional properties, and antioxidant activity of W-IDF were also evaluated, which will provide a new effective method to obtain functional W-IDF to extend its potential application in fields of food processing, and development of functional food.In present study, W-IDF was biologically modified by fermentation with single or mixed strain  was purchased from Aoboxing Biotechnology Co., Ltd . Papain  and ABTS (≥98% ) were purchased from Solarbio Co., Ltd . DPPH (96%) was purchased from Macklin Co., Ltd . Strains: B. subtilis, L. acidophilus, L. Plantarum, or mixed lactic acid bacteria that was L. Acidophilus : L. Plantarum = 1:1) were inoculated at a feed liquid ratio of 1:1 with amount of 5% (~108 CFU/ml). They were stirred then followed by fermentation at 37°C for 48 h.WB was crushed after impurity removal treatment, autoclaved at 115°C for 30 min. After cooling to room temperature, activated microbial strains , shaking for 4 h at 40°C. After filtration, the precipitate was washed. After drying, the obtained WB was kept at −20°C for further analysis.The defatted WB was hydrolyzed with α-amylase (0.02 g/g) at 55°C for 2 h with the condition as following: pH 6.5, material-to-liquid ratio of 1:20 (g/ml). After the hydrolysis, the precipitate was washed with deionized water (DW) for three times, then dried at 70°C to a constant weight.2O2 at 70°C for 4 h, followed by washing the products with DW until neutral and dried at 70°C to obtain different kinds of W-IDF modified with various microbial fermentation which were a blank control group IDF (C-IDF), L. plantarum IDF (P-IDF), L. acidophilus IDF (A-IDF), B. subtilis IDF (B-IDF), mixed lactic acid bacteria IDF (M-IDF), respectively.The dried sample without starch was hydrolyzed with papain (0.002 g/g) at 40°C for 1.5 h with pH of 6, material-to-liquid ratio of 1:5 (g/ml). After the enzymolysis, the fermentation substances were heated in a water bath at 100°C for 5 min to inactivate, then the precipitate was washed with DW for three times and dried at 70°C to a constant weight. Afterwards, decoloration was carried out with 8% H−1, 32 scans, and the resolution was 0.25 cm−1.Fourier-Transformed Infrared Spectroscopy (FT-IR) analysis was carried out to measure the structure of the W-DIF with Use Nicolet iS20 (Thermo Scientific). The infrared spectrum was recorded in the range of 650–4,000 cmThe IDF were examined using scanning electron microscopy (SEM)  at 3 KV. Installed the powder sample on a metal platform with conductive tape and sputter-coated with gold. Images of each sample were taken at 2,000 × magnification.1. The loose density (LD) was measured as the following formula calculation.1.0 g of IDF (m) was added into a 25 ml graduated cylinder at a free falling speed through a funnel with a diameter of 6 cm, measuring its volume as V2, which was then calculated according to the following formula.1.0 g of IDF (m) was poured into a 25 ml graduated cylinder at a free-falling speed through a funnel with a diameter of 6 cm. A wooden board was fixed on the shaker so that the funnel could hit the board, and then the shaker was reciprocated at 120 r/min for 2 h. The resulting volume was the bulk volume V1) was put into a 50 ml centrifuge tube (m0). It was kept at room temperature for 30 min after adding 30 ml of DW. The supernatant was discarded after centrifugation at 2,500 r/min for 10 min, recording the total mass of the centrifuge tube and insoluble dietary fiber as m2. The water retention capacity (WRC) was calculated according to the following formula.Refer to the method of Esposito et al. , 2.5 g o1) was kept in a 50 ml centrifuge tube (m0). After adding 20 g soybean oil, the centrifuge tube was placed at 37°C for 1 h, followed by centrifuging at 3,000 r/min for 20 min. After removing the upper oil, the total mass of the centrifuge tube and IDF was recorded as m2, and then the oil retention capacity (ORC) was calculated by the following formula.According to the method described by Liu et al.  with mod1. 5.0 ml of DW was accurately measured and added. The IDF was suspended in the added DW for 24 h at room temperature. The volume of hydrated IDF was marked as V2. Then the water swelling capacity (WSC) was calculated according to the following formula.Based on the method of Ma and Mu , 0.5 g o−. The filtrate was checked with a 10% AgNO3 solution, and titrated until there was no white precipitate, which proved that the chloride ions have been removed. The filter residue was collected and placed in a drying oven at 60°C with blowing air for drying. 0.30 g of the dried sample was dispersed in 100 ml 15% NaCl solution, and stirred magnetically for 5 min. After adding phenolphthalein (2 g/L) for color development, the solution with was titrated with 0.1 mol/L sodium hydroxide to a light red color, recording the consumption of sodium hydroxide as V1 (ml), hydroxide as V2 (ml), then the consumption volume of sodium hydroxide as V1-V2.The method provided by Carvalho et al.  with sli1, V2 and m was represented as the titration volume of the sample (ml), the titration volume of the blank (ml) and the dietary fiber quality (g), respectively.Where VAs per the previous method Kahlon and Chow , 25 ml o1, m2 and m represented the sodium cholate content before adsorption (mg), the sodium cholate content after adsorption (mg) and the dietary fiber quality (g), respectively.Where mOn the basis of the method employed by Zhang et al. , yolk of1, m2, and m represent the cholesterol content before adsorption (mg), the cholesterol content after adsorption (mg), and the dietary fiber quality (g), respectively.Where m2 solution with a concentration of 1 mmol/L. pH of the systems were adjusted to 2.0 and 7.0, respectively, and kept at 37°C for 2 h with magnetic stirring 0.1 ml of sample solution was applied to determine the Following the method described by Zhu et al. , each 1.1, n2, and m represent the nitrite content before adsorption (μmol), the nitrite content after adsorption (μmol) and the dietary fiber quality (g), respectively.Where nRefer to the method reported by Zhang et al.  with sli2CO3 solution was added, the solution was placed in the dark at room temperature for 60 min. The absorbance at 765 nm was measured, then a standard curve was set up. Measure the absorbance of the sample solution in the same way and calculate the total phenolic content (mg/g).Based on the method introduced by Dong et al. , 5 ml ofWhere C, V, D, and m represent the total phenol concentration (mg/ml), the extract volume (ml), the dilution times, and the dietary fiber quality (g), respectively.1, Replacing the sample solution with absolute ethanol to determine the absorbance as A0. Substituting the DPPH-ethanol solution with absolute ethanol to measure the absorbance value (A2).According to the method described by Xu and Chang , the obtAs per Re et al.  with sli1). The sample solution was replaced with absolute ethanol to determine the OD value (A0), while replacing the ABTS free radical stock solution with DW to determine the OD value (A2).The prepared antioxidant substance mentioned above was diluted five times with DW. 0.9 ml of ABTS free radical stock solution was added to 100 μl of the diluted solution, and mixed well, followed by keeping in the dark at room temperature for 5 min. Its OD value was determined at 734 nm . Origin 2021, SAS 9.2 were used for drawing and ANOVA difference analysis.−1 was significantly reduced compared with C-IDF. Honcu et al.  images of the modified and unmodified W-IDF were shown in p < 0.05). As shown in p < 0.05). The ORC of M-IDF (3.86 g/g) and P-IDF (3.71 g/g) were also significantly higher compared to the one of C-IDF (3.50 g/g) (p < 0.05)  . As showp < 0.05) , the cation exchange capacity (CEC) of fermentation modified group was significantly improved ( < 0.05) . Among tp < 0.05). The modified P-IDF and A-IDF's ability to bind bile acid was improved, which not only greatly reduced the raw materials for synthesizing cholesterol, but also directly reduces the cholesterol content in the body.The adsorption capacity of IDF for sodium cholate (SCAC) was shown in p < 0.05). Except for A-IDF, CAC at pH 7 was greater than the one at pH 2, indicating that the acidity and alkalinity of the system also had a greater impact on the ability of DF to adsorb cholesterol.Cholesterol adsorption of capacity (CAC) of W-IDF at different pH was summarized in p < 0.05). For all W-IDF, NIAC at pH 2 (simulating human gastric juice environment) was significantly stronger than that under pH 7 environment.As shown in p < 0.05). Among them, M-IDF (2.39 mg/g) revealed the largest TPC, which was 1.65 times that of C-IDF.The determination results of total phenolic content (TPC) for different IDF were summarized in p < 0.05).As shown in p < 0.05).As shown in L. acidophilus was stronger than the one with other three. This may result from its strong acid production ability, which exerts a great impact on the arrangement of chemical bonds of W-IDF. After fermentation modification, structural changes possibly arised from the enzymatic hydrolysis that removed the protein or starch around the IDF. Meanwhile, the acid production of lactic acid bacteria caused degradation to cellulose and hemicellulose , which improved the physical, chemical, and functional properties of IDF. After fermentation by The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.A-ML: formal analysis, investigation, data curation, writing-original draft, and funding acquisition. JZ: investigation, data curation, and writing-original draft. Z-LY, X-XL, P-HZ, Y-QD, and Z-YH: investigation and data curation. LP: software and formal analysis. Y-CH: data curation and writing-review. MH: writing-review and editing. J-HH: visualization, project administration, writing-review and editing, funding acquisition, and supervision. All authors contributed to the article and approved the submitted version.Y-CH was employed by Henan Cooperativity Medical Science and Technology Research Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Acid soils are a major constraint to agricultural productivity in many parts of sub-Saharan Africa, including Ethiopia. Restoring soil pH to optimal ranges for agriculture can have a significant impact on yields, particularly for acid intolerant crops like wheat and barley. The application of agricultural lime is the standard corrective, although the large application requirements, lack of farmer awareness, and weak or non-existent lime supply chains make this a complex problem to address at scale. To date, no large-scale farmer trials of lime application have been undertaken in Ethiopia. This leaves open the question to local policy makers as to the economic benefits given the enormous capital and logistics investments required. To help address this we leverage existing spatial edaphic data and longitudinal crop surveys to simulate the productivity impact of varying lime and fertilizer applications. Our estimates find the impact of moving pH from 5.5 to 6.5, modeled as a lime soil remediation strategy, increases yields by 22% and 19% for wheat and barley, respectively. In addition, at lower pH levels our models indicate that commonly used nitrogen-based fertilizers are less cost-effective. For wheat in highly acidic soils, we find that fertilizers cost over two times as much as a single application of lime over a five-year period. The cost savings of the use of lime reaches as high as 121% of average one-year agricultural household income for wheat; with barley these savings are lower but still substantial at 24%. In general, we advocate for an integrated soil fertility management strategy that applies appropriate levels of fertilizer on pH balanced soil. If successful, Ethiopia’s acid soil reclamation could become a modest version of Brazil’s successful “cerrado miracle” and serve as an example for Africa. Over decades of intensive utilization, small-scale farmers in Africa have removed large quantities of nutrients from their soils without sufficient inputs to replenish them , 2. EvenSoil acidification is a major cause of declining soil fertility in many parts of the humid sub-tropics, particularly in tropical Oxisols and Urtisols soils. Soils become acidic when basic elements such as calcium, magnesium, sodium and potassium held by soil colloids are replaced by hydrogen ions. This removal of bases can occur through natural processes, such as leaching caused by rainfall, or anthropogenic processes, such as intensive use of ammonium-based fertilizers and continuous cropping without organic inputs , 4. The Acidification has a number of direct and indirect effects on plant health and development. Correcting soil acidity through the use of lime can serve as a foundation of a good soil fertility program. Maintaining proper soil pH has a variety of primary and secondary benefits including critically, increasing yields and the stimulation of microbial activity. In some experimental wheat plots, lime application can increase root length density by >100% and yields by up to 200% . Most vaAreas of high acidity are located throughout the western Ethiopian highlands, but particularly in the western and central highlands of Oromia and Amhara –13, and Lime is often referred to as the foundation or “workhorse” in acid soils , and a mField studies inside of Ethiopia and other developing nations have found consistent benefits of lime application, including the expected reduction of acidity , 25. TheIn this article we aim to partially address the information gap created by the lack of large-scale national lime trial research. We do this by leveraging statistical methods and exploiting the natural spatial variability in pH and existing longitudinal crop productivity data. We focus on wheat and barley because they are among the most important cereal crops grown in Ethiopia’s highlands. Given the resource constraints of agricultural interventions in Ethiopia specifically, but Africa more generally, we compare the cost effectiveness of commonly used fertilization methods with the potential impacts of soil remediation through the application of lime. Specifically, we evaluate the quantity and cost of annual fertilizer applications required to obtain the same productivity gains from a single lime application over a five-year period. This comparison is not to argue for an “either or decision” e.g., choosing between lime and fertilizer, but critically, to explore whether or not lime should be considered an important and cost-effective intervention in Ethiopia. As an important caveat, it is critical to acknowledge that our analysis uses secondary data projected over the sub-kebele area and is not at the individual plot level. While this level of aggregation depicts general impacts of pH and crop productivity, we believe the potential impacts of lime and pH balanced soil on crop productivity would be greater at the plot level. We cannot directly assess the application of lime as a corrective because it is largely unavailable to farmers. Therefore, we estimate the marginal effects of lime exploiting the spatial variability of soil pH and their resultant differences in reported crop yields, as an imperfect, yet meaningful, proxy.In this analysis, we leverage statistical methods and spatial variability in pH, coupled with longitudinal crop-cut data, to model the yield responses of wheat and barley. Our basic strategy is to use empirical insights about these crop-specific yield-pH relationships, in concert with reasoned assumptions about soil pH responses to lime, as the agronomic basis of a location-specific cost comparison of two alternative interventions, lime and fertilizer. We explore both the extent to which–and where–farmers would benefit from the application of lime to increase yields in comparison to yield gains attainable through nitrogen (N) fertilizers. Specifically, this analysis provides a comparison of the present value or “current cost” of lime to that of fertilizer required to provide the same yield gain over a five year-period. Present value is the current value of a future flow of money discounted to take into account for compounding at some specified rate of return (discount rate). In this case it is the “current cost” of future payments for lime or fertilizer application(s), or the amount you would need to hold aside today to make these purchases.Our analysis uses annual agricultural production data from the Central Statistical Agency’s (CSA) Agricultural Sample Survey (AgSS) between 2010 and 2016 . For thiData on soil properties were collected from the Ethiopian Soil Information System (EthioSIS). EthioSIS was charged with gathering soil samples from all major growing regions to help provide detailed information on soil fertility, and to provide localized fertilizer recommendations . For thiThis study controls for the impacts of drought and elevation with remotely sensed data. We obtain hydrological variables from the University of Idaho’s TerraClimate data  and utilTwo dummy variables were used to capture areas impacted by national agricultural policy interventions which receive targeted external support. These two programs include the Agricultural Growth Program (AGP) for high potential growth areas, and those designated for social protection programs using the Poverty Safety Net Program (PSNP). We also control for the major agroecological zones of Ethiopia with data from The Water Land Resource Center  AdditionFor operational purposes, it is important to point out that pH measures only a portion of a soil’s acidity and should not be exclusively used to determine lime requirements. To better measure needed lime requirements the soils “buffer capacity” is projected as a function of sub-kebele values of CEC as well as base saturation estimates values determined by a pH-base saturation model .To estimate lime application rates needed to raise pH levels to the desired levels, there are at least seven items to consider in the Ethiopian context , shown iL is the lime required (mt/ac) can be determined by: cation exchange capacity (CEC), BSt and BSo are the target and original base saturation rates at the current and at the desired pH, respectively, tillage depth (TD) in inches, calcium carbonate equivalent (CCE) of the chosen lime material, relative fineness of the liming materials (F), and adapting estimates to Ethiopian conditions.Where Details on the use of this formula for estimating the amount of lime required to obtain a pH of 6.5 are outlined in section E of Bivariate plots are used to help frame the discussion of the relationship between yields and fertilizer or lime applications. We use sub-kebele level observations from the AgSS, pooling data from the 2010–2016 growing seasons. Because there are thousands of observations, they are summarized with Loess smothers. In each figure the colored lines are the result of Loess smothers tracing the non-linear relationship between the observations of the x and y factors, and the 95% confidence intervals are in gray. These plots, while informative, are simplistic as the impacts of any variable should be evaluated in a multivariate context.M1 is sufficient to explain the data against the hypothesis that a more complex model M2 is required. In our yield response model, we control for a variety of independent variables. These are defined In order to examine the marginal effect of grain output per hectare to changes in soil acidity, we control for the effects of other variables such as water availability, soil properties, elevation, policy interventions, and management differences. To do this a regression is used on all sub-kebeles for 2010–2016 with year and agricultural zone fixed effects. This regression allows us to examine how a one unit increase in fertilizer or pH relates to wheat or barley yields while controlling for other potential determinants of productivity. To better address the highly non-linear nature of many of these relationships, polynomials are applied to all independent variables. The order of the polynomial is established using recursive nested ANOVAs to test the hypothesis that a model In order to test the sensitivity of these regressions a number of alternative specifications are presented in A key part of our approach is recognizing that, like agronomic response, the economic returns to lime application differs by location. This is particularly salient in a country like Ethiopia, where complex terrain and market access have important implications for marketed prices and, consequently, the economic attractiveness of productive investments . In our Because the market for agricultural lime has not yet been developed in Ethiopia, market prices are not available. We therefore estimate the distribution costs of delivered lime to cooperative unions or other private input distributors on the basis of current crusher locations at Butajira, Guder and Dejen. One metric ton (mt) of lime at each crusher location was assumed to cost 750 Ethiopian Birr (ETB). To conform to our period of analysis, we use December 2016 exchange rates ($1 = 22.07 ETB). From each crusher location, the cumulative travel time from all locations in the country was calculated on the basis of a spatial cost-distance model, which factored in road network data , discounTo understand differences between the cost of lime and fertilizer we need some normalized basis of comparison. To do this we estimate the marginal response in yields, corresponding to differences in pH and fertilizer for wheat and barley. We then estimate, for the average sub-kebele hectare, how much it would cost to reduce acidity from, for instance, a pH of 5.5 to 6.5 through the application of lime, and the average yield response of this intervention measured in mt/ha. In contrast, we can also estimate the amount and cost of fertilizer required to obtain the same yield response (mt/ha) expected from that lime treatment and compare them. This comparison is presented throughout the paper as ‘X Cost of Lime,’ and is the economic costs of fertilizer divided by the cost of lime—for some specified yield response—typically that of bringing the observed pH up to 6.5.To compare the costs of lime and fertilizer, it is critical to note that fertilizers require annual applications, while lime is assumed to be applied once every five years. Fertilizer applications therefore need to be thought of as a repeated annual cost over a five period, subject to a present value calculation.For present value calculations we assume that the annual costs of Urea and NPS fertilizer are 11.5 ETB/kg or 0.52, reflecting costs during our period of analysis (Dec. 2016). These costs are discounted across five years, at an annual discount rate of 8% and an inflation rate of 13.4%. These rates reflect savings interest rates and consumer price indices during our time period of interest , 45.To test whether our data conform to the established relationship between pH and wheat and barley yields, we explore the relative yields and pH, at the sub-kebele level. Consistent with literature, we see a concave response of yield to pH for wheat and barley, both peaking near 6.5. However, yields, are impacted by a number of edaphic and management variables. To test if wheat farmers are adapting to highly acidic soils by applying more fertilizer, we plot observations of intensity of fertilizer use (kg/ha) against soil pH for wheat in This variety of regional responses to pH likely reflects local policy and extension approaches to address lower than expected yields. Anecdotal evidence from a former Amhara official suggests that fertilizer was heavily emphasized over balancing soil pH to boost flagging yields. Although suggestive, the effectiveness of these mitigation strategies will depend on the relative costs of annual fertilizer applications, and the frequency of lime application. Given this finding, farmers utilizing greater than average amounts of fertilizer, especially urea, may now be suffering from “induced acidification” especially in Amhara and Tigray. Induced acidification occurs during the growth period when crops absorb basic elements such as Ca, Mg, and K to satisfy their nutritional requirements, and removing these lime-like nutrients .from 5.5 to 6.5, with approximately 3.12 metric tons of lime per hectare. The amount of lime required is approximated using the trend line in Fig A1 in Based on expert opinion from soil scientists knowledgeable about Ethiopian soil conditions, we can estimate the cost of lime to move the pH one unit, Estimation results from the model described in the “Multivariate Estimation Strategy” section are shown below . This reTo isolate the marginal effect of pH and fertilizer on yields, we hold all other variables at their mean (fixed effects variables are set to a specific year and zone), while letting the variable of interest vary. As expected, highly acidic soils (low pH) show low levels of productivity, increasing significantly with higher pH, until an inflection point. Response curves from models 1 and 3 are shown below. Because lime is largely unavailable to most farmers, these curves are based on spatial variability in observed pH and yields, rather than on plot-level applications of lime. As such, they are indicative of the impact of lime, and are not definitive results. As such, our spatially aggregated results likely underestimate relative responses at the individual household level. Further research, at the plot level of the representative farmer using lime, is strongly recommended.To understand the response of yield to changes in pH in a multivariate context, controlling for weather management and edaphic properties, we plot the estimated response curve from models 1 and 3 in Polynomial estimates in The yield gains obtained from the generalized case of moving soil pH from 5.5 to 6.5 for both crops are presented in We can also look at the spatial distribution of productivity gains based on actual pH levels. To evaluate the marginal response of yields to fertilizer applications, we plot the estimated curves from models 1 and 3 in The impacts of lime application will vary, following the spatial patterns of soil pH at the sub-kebele level. As such, there is a great deal of variability within and between regions. Careful lime targeting will be required for an effective intervention. While there are “moderately” (5.5 < pH ≤ 6) acidic soils throughout our four regions of study, our AgSS sample in Tigray covers no moderately acidic areas and a relatively small number of highly acidic ones. This reflects the general lack of non-acidic soils in the Tigray regions as seen in To better understand the spatial variability in yields obtainable by increasing the current pH to 6.5, we use the polynomial estimates from models 1 and 3 and plot the results in Differences in In this section, we compare the present value of applications of lime and fertilizer required to obtain the same yield increase .Taken as a whole, there is substantial evidence that soil remediation can increase yields and economic outcomes for farmers across its acidic regions. These findings do not argue for an “either or decision,” choosing between lime and fertilizer, but instead demonstrate that lime should be considered an important and cost-effective intervention in Ethiopia. Extensive research indicates that balanced pH is an essential prerequisite to optimal crop yields, especially for crops such as wheat and barley . TherefoS1 File(DOCX)Click here for additional data file.


Qualitative research and comprehensive public awareness to nip the transmission of Ebola virus in the bud before it becomes a global threat is fast becoming imperative especially now that the Gambia Ebola virus is mutated. It is therefore necessary to consider and investigate a vector-host transmission model for possible control strategy of this deadly disease. Hence, in this study, we presented a novel and feasible human-bat (host-vector)  Ebola; Stability; Endemic; Control strategies; Optimal control Through close contact with a fluidic component of the body, such as discharges, blood, organs or tissues, etc., of infected animals like sick or hungry chimps, raccoons, monkeys, chimpanzees, forest antelope, or fruit bats found unwell or hunted for food in tropical regions, this virus slips into the human host. In many parts of Africa, gaming is a large-scale business, and bats which happen to be a big reservoir and transmission vector of the Ebola virus are hunted for food. Despite the concentration of earlier research on within-host control measures for the deadly infection, the threat flagged by the recent cases of Ebola infection in DR Congo after many months of WHO declaration of her Ebola-free status makes curbing of transmission of infection of the virus seems to have defied all logic. Hence, further study of possible control strategies cannot be over-emphasized as this will go a long way to curb the explosion of infection, short down possible transmission routes, remove avoidable pressure on health facilities, and subsequently save lives and costs Studies have proven that the During the year 2014–2016, Ebola virus disease (EVD) was recorded to have killed numerous people in Africa specifically in the western part. Over 16,000 analytically confirmed cases with an estimated value of 70% death rate in the affected population. The exacerbating situation of EVD was declared by the World Health Organization (WHO) on August 8, 2014, in West Africa – Public Health Emergency of International Concern (PHEIC). A sum of 28,616 cases of Ebola virus disease with 39.5% mortality rates was reported in Sierra Leone, Guinea, and Liberia in 2016. The upsurge of the Ebola virus was identified in Nigeria precisely in July 2014. The dynamic transmission of the Ebola virus disease was observed to have a breakout in seven countries are United States, Mali, the United Kingdom, Nigeria, Spain, Italy, and Senegal Numerous deterministic and stochastic models have been developed by different researchers to study the dynamic transmission, effect of vaccination, and optimization of EVD From a set of seven potential vaccinations, two operative candidate vaccines have been developed and clinically tested through several studies As a departure from studies in existing literature on Ebola virus diseases where there is concentration on within-host transmission dynamics, we present a feasible and noble ordinary differential equations based system, 2Bifurcation analysis and dynamical behavior of a saturation incidence rate Ebola virus model are shown in 2.1N’ of the system has been subdivided into ‘In our model, the total population ‘la virus .Figure 1c is the likelihood that a person will only fully recover in isolation once the virus has entirely left the fluidic portion of their body. The chance of a recovered human being out of isolation before the virus has completely left their body's fluidous portion is known as  and (3) are non - negative for all, with the initial conditions as described in equation (4).ProofLet Assume As From the first equation of 3.2Theorem 2All systems of equations–have bounded analytical solutions.ProofImplementing Grownwall's inequality according to This implies,Then4The fundamental reproductive number Considering equation χ since they can still have Ebola virus in the fluidic part of their body for some time. So, they have the possibility of transmitting the virus to susceptible individuals. Though, the transmission dynamics is minimal in LetHence, from 5The occurrence or existence of the DFE points indicates that the population as a whole is totally susceptible to the stable-state case in which the Ebola virus infection fades out.That is At the DFE point at 5.1Theorem 3The Disease Free Equilibrium (DFE)of the system is said to be locally asymptotically stable if all eigenvalues of the systems generated Jacobian's matrix are negative real values.ProofThe Jacobian matrix Step-by-step row operation on subsequent matrices  Since We advance from the eigenvalue 5.2Theorem 5implies the disease-free-equilibrium (DFE) of system–is globally stable on M.ProofTo prove this important theorem, we implement the method used in We start by dividing the system of equation LetB as an M-matrix where the off-diagonal element is not negative.With When we consider the system that were reduced, M and so:(27) Equations The solution of 5.2.1Theorem 6System–express a distinct EES,if.At equilibrium; From the system of equations Let From 6Recall from We now introduce control measures σ the probability of infection, the system Let 6.1H) establishes the most effective of the strategies presented: complete abstaining from touching the deceased from Ebola infection , an outright ban on bat hunting for food, and deliberate depopulation of bats in cities by specialized teams and immediate treatment of the infected individual in isolation. These measures are analytically presented to be feasible in minimizing the transmission of this deadly virus in a finite time interval Using Pontryagin's maximum principle H as follows:We define the objective functional Where T is the final time and parameters In the objective function, To achieve the objective of the control problem, we implement the function such that6.2Theorem 7Considering the objective functionalas inabove where the control set K is measurable subject towith the initial condition given at, then there exists an optimal controlsuch that.ProofH to optimize control Resulting from the convexity of the integral of L) and Hamiltonian (H) for the optimal control problem.Now we will need to establish the Lagrangian With transversality conditions,which imply the control functions are:Where(40)To obtain the adjoint equation and the conditions for transversality, we differentiate the Hamiltonian with respect to the state variables and obtain the following equation:(41)With the conditions for transversality. To reduce the Hamiltonian (H) with regards to the optimal controls, we apply the idea of differentiation, i.e., H is differentiated with respect to,and.Equating the results to zero gives the solution. This provides the required optimization measures and putting in the boundary condition of each of this control gives:7In this study, we created a mathematical model for the dynamic spread of the Ebola virus disease, and we included three preventative strategies. We examined and presented the mathematical analysis of the model with (out) the control measures. The stability analysis carried out showed that the disease-free equilibrium is locally asymptotically stable if The following is a summary of the potential impacts of the included control strategies.8Earlier research concentrated on within-host transmission dynamics and possible control strategies for the Ebola virus. In this study, we presented a novel vector-host mathematical model, particularly the human-bat model which forecasts the transmission and severity of the Ebola virus from bats to human to analytical study the impact of some control measures that would help stamp out the transmission of Ebola virus. We considered strategies which include systematic and deliberate depopulation of bats  from the cities to avoid hunting them for food by virtue of their proximity, immediate isolation of infected individuals for treatment in case of an outbreak and complete abstaining from touching the remains of patients who died from Ebola virus irrespective of their social affiliation hence allowing designated agencies to handle the burial to prevent post-death transmission. We showed the presence of optimal control, proved the feasibility of the model by validating parameters cogent in mathematical epidemiology, and also presented results that remarkably show that the front liners and government agencies are better informed in their decision making as to the possible control strategies to adopted in their battle against Ebola virus in a vector – host situation to arrive at a healthy population.Joshua Oluwasegun Agbomola: Conceived and designed the analysis.Adedapo Chris Loyinmi: Analyzed and interpreted the data; Contributed analysis tools or data; Wrote the paper.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.