A first generation of CRISPR-based gene drives has now been tested in the laboratory in a number of organisms, including malaria vector mosquitoes. Challenges for their use in the area-wide genetic control of vector-borne disease have been identified, including the development of target site resistance, their long-term efficacy in the field, their molecular complexity, and practical and legal limitations for field testing of both gene drive and coupled anti-pathogen traits. We have evaluated theoretically the concept of integral gene drive (IGD) as an alternative paradigm for population replacement. IGDs incorporate a minimal set of molecular components, including drive and anti-pathogen effector elements directly embedded within endogenous genes – an arrangement that in theory allows targeting functionally conserved coding sequences without disrupting their function. Autonomous and non-autonomous IGD strains could be generated, optimized, regulated and imported independently. We performed quantitative modeling comparing IGDs with classical replacement drives and show that selection for the function of the hijacked host gene can significantly reduce the establishment of resistant alleles in the population, while drive occurring at multiple genomic loci prolongs the duration of transmission blockage in the face of pre-existing target site variation. IGD thus has potential as a more durable and flexible population replacement strategy. Summary: Here, we describe and model a novel gene drive strategy – integral gene drive – for population replacement based on the hijacking of endogenous genes. Homing gene drives were first proposed 15 years ago as potential tools for enabling the genetic engineering of natural populations , in partAlthough gene drive research is now mainly centered on drives built using the CRISPR genome-editing toolset, proposed strategies adhere to the classic transgene paradigm, namely the use of pre-characterized promoter and terminator elements, each driving tissue-specific transgene expression as required for different functions in the germline (drive) and various somatic tissues (anti-pathogen effect), and with the resulting constructs inserted at arbitrarily chosen genomic sites, e.g. genes that are presumed to be neutral A. It hasPlasmodium transmission. A growing set of anti-pathogen effectors now exists . Each IGD effector transgene also carries a ubiquitously expressed U6-driven intronic gRNA for triggering homing in the germline. Unlike the drive component, however, the effector component does not encode an endonuclease and thus is not able to initiate gene drive on its own. Indeed, targeted cleavage mediated by the gRNA and Cas9 complex can only occur when the latter is provided by the drive component in the germline. Cleavage in the germline triggers homing of the effector component, which is a non-autonomously homing allele of an endogenous gene and is designed to spread in a population, thereby increasing the allele frequency of the coupled effector trait. We define non-autonomous gene drive as the ability of a certain allele, encoding a gRNA that renders itself capable of homing, to only show gene drive, provided that a Cas9 endonuclease is supplied by another genetic element.For simplicity, we consider here the effector to be an exogenous polypeptide that when expressed in the target tissue reduces or abolishes parasite development in the mosquito. Various mosquito tissues – such as the midgut, the hemocytes and the salivary glands – are at the interface of the vector-parasite interactions and are thus ideal candidates for hosting the expression of effectors. The fat body is another good candidate tissue, as its secretions into the hemocoel can directly interact with  parasiteDrive and effector traits inserted at various suitable loci throughout the genome could be generated and tested independently from each other, including by different research teams. On the one hand, the drive component can be specifically optimized in the laboratory for its propensity to induce homing, the faithfulness of Cas9 expression and to minimize the rate at which cleavage triggers the undesirable non-homologous end joining (NHEJ) or microhomology-mediated repair (MHMR) pathways. In addition, one would seek to reduce the fitness cost incurred by the expression of Cas9 itself or by its integration interfering with the function of the hijacked host gene. On the other hand, the effector component can be optimized in the laboratory for its efficacy in reducing or blocking parasite/pathogen development and transmission, its own intrinsic fitness cost and any negative effect it may have on the expression of the hijacked host gene. In addition, the rates of non-autonomous homing of the effector component, assisted by the presence of the IGD drive component or another source of Cas9, can be measured under laboratory containment. Laboratory crossing of the transgenic strains harboring the IGD drive and effector components would allow assessing the likely performance of these trait combinations in the field, including the spread of each modified allele and their resulting frequency in cage populations. It should be noted that the existence of independent IGD strains requires them to be appropriately isolated to minimize the risk of them combining before it is desired.To predict the behavior of one or multiple interacting IGD traits at the population level, we used a discrete-generation (non-overlapping) model, comparing the dynamics of a classic replacement drive  to the dn) of expression due to the nuclease is less than the cost (se2) of expression for the effector (sn=0.05 versus se2=0.1), resistance replaces the transgene faster at the effector locus, while the nuclease persists for longer in the population, whereas in the conventional strategy, the compound cost for expressing both causes the construct to be lost rapidly. We find that at the same rate of formation of resistant alleles, their impact is reduced in the IGD strategy since mutations that result in a loss of function of the hijacked endogenous target gene and are selected against – unlike the conventional strategy, which assumes the target to be neutral.A comparison of a conventional replacement strategy and the IGD two-loci model is summarized in Fig. S2). We find similar dependencies as for the classical model; however, for a number of parameters IGD appears more robust with minor or no effects on the duration of protection evident. For example, increasing the proportion of resistance and loss-of-function alleles formed by either NHEJ or aberrant HDR at locus 1 within a biologically sensible range does not affect the duration of protection. This can be explained by the main effect the drive component (locus 1) has on locus 2, which is to convert wild-type alleles to effector alleles in heterozygous individuals, allowing the effector to rapidly propagate in the population and to establish protection before resistance at locus 1 takes over. Protection starts decreasing only when resistant alleles start forming at locus 2 and eventually replace effector alleles in the population. The eventual subsequent loss of the drive allele at locus 1 and its replacement by resistant alleles is no longer of any consequence to the duration of protection because the conversion of wild-type alleles at locus 2 into effector has already taken place.In order to determine which parameters have the strongest effect on the duration of protection, we varied each while retaining all others at baseline values . By contrast, levels of protection begin to crash only when initial resistance at locus 1 approaches 80% i.e. that target sequence represents a minor allele. Should pre-existing resistance alleles occur with a frequency of 10% at both loci, 95% protection is reduced from 81 generations to 15 generations. Pre-existing resistance must be assumed to be present in significant proportions in many target species including mosquitoes , the longer it will be present in the population and the longer protection can be extended. The condition for full protection to be achieved after release of the second effector at locus 3 is that the allelic frequency of the nuclease is greater than ≅55% at the time of release. If the second effector is released before protection starts significantly decreasing, it can optimally prolong the duration of maximal protection. We find that the ideal time for secondary effector release at locus 3 is when protection drops below 95%.A second effector component allele at a separate locus could also be introduced after a given time to extend the duration of protection. The second effector is driven through the population when in the presence of the nuclease allele at locus 1, extending the duration of protection until the time when the second effector is in its turn replaced by resistant alleles. The IGD paradigm reflects our view that a successful gene drive intervention will have to involve the use of multiple interacting traits rather than attempting to make singular constructs evolution safe. It consequently should allow (informed by continuous monitoring) the ability to flexibly react to predictable as well as unexpected developments in a target vector or parasite population by adapting the release strategy in a context-dependent manner. Control would require the constant development and refinement of engineered genetic traits rather than the one-off or continued application of a static product.Modeling of allele frequency dynamics suggests that for the parameters investigated, the IGD strategy could confer significant advantages over conventional replacement drive designs. By integrating components into endogenous loci, undesired repair outcomes following DNA cleavage are predicted to result in loss of function of the hijacked gene. Selection, in turn, reduces the rate at which such resistant alleles accrue. Whilst IGD does not prevent the onset of resistance, it could significantly extend the duration and level of protection available to the human population. This approach also could resolve the longstanding issue of the arbitrary selection of a target sequence for population replacement where neutral sites show poor conservation, whereas conserved sites are likely to be functionally constrained and thus costly to disrupt. For example, trying to tackle this conundrum, Gantz and colleagues disrupt the kynurenine hydroxylase gene in their replacement approach with unclear consequences for the behavior of these drives in the field . The IGDns=0.05) is lower than the cost of expressing an effector gene from an effector component (es2=es3=0.1). This is justifiable when considering that germline genes tend to have lower expression levels than those present in the soma and that expression of antimalarial effectors needs to be sufficiently strong to ensure effective concentrations. Probabilistic models of finite populations (versus our deterministic model for an effectively infinite population) predict that resistant alleles generated at low rates suffer early stochastic loss , the cost of disrupting the drive component locus (d1s), the cost of expressing the effector (es) and the cost of disrupting its corresponding locus (d2s). Modeling shows that changes in the cost of expressing the nuclease and the cost of disrupting the drive component locus are robustly tolerated. By contrast, the IGD strategy is sensitive to changes in the cost for disruption of the effector component locus, and the cost of expression of the effector. This is due to the efficiency with which the drive component, even if not present at high allele frequencies, is able to convert wild-type alleles into effector alleles. Thus, even if the drive component carries significant costs of expression and disruption, there will not be a sizable reduction in the duration of protection. These findings may be useful in the design of IGD traits, particularly with respect to the effector components. Minimizing the cost of effector expression and avoiding disruption of the hijacked gene are critical to the successful implementation of an IGD-based release. Previous work has highlighted the difficulty with which these parameters can be evaluated in a field setting , including an independent ecological risk assessment. It is expected that gene drive strains will face a significantly tougher and prolonged regulatory pathway compared to strains harboring such a conservative genetic modification. These foreseeable regulatory and operational challenges must inform the design of gene drives, and the potential theoretical properties of IGDs should thus be considered in conjunction with the practical aspects of generation, testing, optimization, regulation and deployment of gene drives for population replacement.Recently, the first transgenic mosquito strain, carrying a dominant male-sterilizing transgene , was impField testing of the effector component would be aided by the simplicity of the genetic modification, i.e. insertion of a single effector coding sequence containing the intronic gRNA, with all other functions provided by the hijacked host gene. Given the inability of the effector component to spread autonomously, the regulatory threshold for such strains is expected to be lower than that of conventional fully driving transgenes harboring a population replacement payload A. This wThe scientific working group on a pathway to deployment of gene drive mosquitoes for elimination of Malaria in Sub-Saharan Africa  recommenThe IGD strategy offers an increased degree of versatility by allowing independent testing and release of overall less complex components. The scientific working group on gene drives recommends a stepwise pathway for the deployment of gene drive mosquitoes i.e. to progress testing from laboratory studies, possibly involving large indoor and outdoor cage trials, to small-scale isolated and open releases to full-scale open releases . HoweverThe modularity and interdependence of IGD components does provide a straightforward path for moving testing from self-limited to self-sustaining traits in the field by modulating the propensity to spread in the population . First, https://github.com/genome-traffic/igd. The classical model for a drive+effector construct  considei . Locus 1 corresponds to the drive component, and loci 2 and 3 correspond to effector components. At each locus i, there are four possible alleles: a wild-type allele (iw), a transgene it , and two types of alleles at each locus that are resistant to the drive and do not have an intact nuclease or effector, ir and im. The first type of resistant allele, ir, arises from incomplete homing or mutations that are in-frame and do not cause loss of the function of the host gene, and therefore are not considered to carry any fitness cost (similarly to the wild type). The second type of resistant allele, im, corresponds to a mutation that results in frameshift of the host gene, disrupting the endogenous locus. If the host gene is an essential gene, im alleles are considered to convey lethality when homozygous. Resistance can be pre-existing or occur either by NHEJ or by incomplete HDR at either locus. We neglect resistant alleles created from spontaneous mutations, as rates are likely to be low, compared to generation of resistance during homing.While the IGD model may involve multiple nuclease genes and effectors on many different loci, here we consider a simplified version with transgenes on either two or three independent loci An individual is considered to have IGD drive if it carries at least one functional drive component at locus 1 and at least one functional effector component at locus 2 . This is a necessary condition for the effector component to home and propagate in the population at a super-Mendelian rate. For both models, we assume that the initial field population consists entirely of the wild-type allele, and there may be pre-existing resistance due to standing genetic variation at each locus . Individuals homozygous for different IGD drive components are subsequently released as a relative proportion of the field population.w1/n1 at the first locus). Cleavage and homing at effector locus 2  can occur only in those genotypes if there is at least one nuclease allele at locus 1 and a wild-type and effector allele at locus 2 (w2/e2 at locus 2). Transmission of the nuclease at locus 1 occurs with probability 1d. Transmission of the effector transgene at locus 2 occurs with probability 2ad when the drive component is heterozygous, and probability 2bd when homozygous, and similarly for an effector at locus 3 if included (3a d3bd). Resistance to the drive, sometimes accompanied by loss of gene function, is considered to occur during homing. We conservatively consider mutations to produce resistance (ir) in 1/3 of cases, and loss of gene function (im) in 2/3, here predominantly caused by frameshift mutations. Resistant alleles (ir) arise at loci 1, 2 and 3 from incomplete HDR with probabilities 1l, 2l and 3l, and by NHEJ with probabilities 1u, 2u and u3, respectively. Resistant alleles (im) that cause loss of the endogenous gene function occur via incomplete HDR at loci 1, 2 and 3 with probabilities 1L, 2L and 3L, and by NHEJ with probabilities 1U, 2U and U3, respectively. Due to germline cleavage, homing, incomplete HDR and repair events, individuals that are heterozygous for the nuclease at locus 1, i.e. w1/n1, contribute alleles 1:n1:r1:m1w in proportions (1−1d) (1−1u−1U):1d (1−1l−1L):(1−1d) 1u+1 d1l:(1−1d) 1U+1 d1L. Allele contributions from individuals with the wild-type and effector allele (w2/e2) at locus 2, if there are one or two nuclease alleles at locus 1, are according to w2:e2:r2:m2 in proportions (1−2kd)(1−2u−2U):2kd (1−2l−2L):(1−2kd) 2u+2 d2kl:(1−2kd) 2U+2 d2L, where k=a, and b corresponds to locus 1 heterozygous or homozygous for the nuclease. If no nuclease allele is present at locus 1, gene transmission at locus 2 is Mendelian, as is inheritance in all other individuals. Similar expression can be written for an additional effector at locus 3.Cleavage and homing can occur only in the germline of genotypes with a wild-type and nuclease allele at locus 1 , which has a fitness of one. Fitnesses are modeled using ten parameters for transgenes at two loci and 14 parameters for three loci. We consider the following homozygous fitness costs: the cost of in-frame disruption  at locus 1, 2 and 3 , the cost of disruption (by mutations of type im) that lead to loss of function at each locus , the cost of expressing the nuclease from the drive component (ns) and the cost of expressing the effector from the effector components . The corresponding dominance coefficients are d1h, d2h, d3h, mh, nh, e2h and e3.h The range of fitness costs is from 0 (no cost) to 1  and dominance coefficients range from 0 (completely recessive) to 1 (completely dominant). The fitness of each genotype is derived as the product of costs at each locus associated with site disruption, number of nuclease components and number of effector components. For example, for a two-loci model (drive at locus 1 and effector at locus 2), the fitness of a genotype that is heterozygous for the transgene at both loci  is given by (1−d1 sd1h) (1−d2 sd2h) (1−n snh) (1−e2 se2h) to reflect costs of host gene disruption by transgenes  at both loci as well as the cost of expressing the nuclease (at locus 1) and the effector (locus 2).With four possible alleles at two independent loci, there are 16 gamete types and 100 diploid genotypes; for three independent loci, there are 64 gamete types and 1000 genotypes. The fitness of each genotype is relative to the wild-type homozygote (Allele frequencies and genotype abundances are modeled using deterministic discrete-generation recursion equations. We assume a one-life-stage model (adults) with a field population composed of equal numbers of male and females with the same genetic and fitness parameters, such that allelic and genotypic frequencies are equal between them. Mating is random, with unsuccessful mating events not considered. We assume the population to be sufficiently large to ignore stochastic effects. The system of equations is solved numerically using Wolfram Mathematica .rc1rch if the effector component is present at locus 2 in one copy (heterozygous) and by cr if two copies (homozygous) are present. For the three-locus model, we assume that the reduction in vector competence depends on the total number of effector alleles, giving rci rch for i=1, 2 or 3 effector alleles in total over loci 2 and 3, and cr for i=4 alleles in total (i.e. homozygous for the effector element in both loci). Values of cr range from 0 (no effect) to 1 , and the dominance coefficient for refractoriness rc1h (and rc2h and rc3h for the three-locus model) ranges from 0 (completely recessive) to 1 (completely dominant). We quantify the effect in terms of the reduction in vectorial capacity at time t as 1−CV[t], where CV[t] is the vectorial capacity. CV[t] is calculated as the sum over the genotype frequencies multiplied by their individual vector competence. For the two-locus model, this yields:As in


Although there are many overlapping features, pediatric diarrheal diseases can vary in severity, duration, clinical manifestations, and sequelae according to the causal pathogen, which in turn can impact the economic burden on patients and their families. We aimed to evaluate the household costs of diarrheal disease by pathogen in 7 countries.Cryptosporidium, heat-stable toxin (ST)–producing enterotoxigenic Escherichia coli (ETEC [ST only or LT plus ST]), Shigella, Campylobacter jejuni, norovirus GII, Vibrio cholerae O1, age, gender, in/outpatient, and country on total costs to the patient/family.We analyzed data from the Global Enteric Multicenter Study (GEMS), a prospective, age-stratified, matched case–control study of moderate to severe diarrheal disease among children aged 0–59 months in 7 low-income countries; 4 in Africa  and 3 in Asia . Demographic, epidemiological, economic, and clinical data were collected, and a stool sample was obtained for microbiological analysis at enrollment. We used a multivariate generalized linear model to assess the effect of rotavirus, Household out-of-pocket costs were higher in Mali than any other country. Within countries, household cost differences between pathogens were minimal and not statistically significantly different.We found no significant differences in household costs by pathogen. Despite data limitations, understanding pathogen-specific household costs (or lack thereof) is useful, as decision-makers could consider broader illness cost information and its relevance to a particular pathogen’s economic burden and contribution to poverty when deciding which pathogens to target for interventions. Cryptosporidium, Shigella, and Escherichia coli producing heat-stable toxin (ST), either alone or in combination with heat-labile toxin (designated ST-ETEC)—were associated with the majority of attributable disease. Although there is considerable overlap in the manifestations of the various etiologic agents, each bears unique virulence factors that can influence the severity, duration, nutritional consequences, and symptoms of the illness. These features, in addition to the pathogen-specific burden of disease, might influence the health care costs related to diarrheal diseases.Diarrheal diseases are a leading cause of death among children in low-income countries . A varieIn many low- and middle-income countries where diarrheal disease is common, health care costs can represent a significant proportion of household expenditures. No study has yet evaluated household costs of diarrheal disease by comparing multiple pathogens and over several low- and middle-income countries. Moreover, it is not known whether these cost burdens differ by pathogen. If costs to the household differ by pathogen, it may be appropriate to target prevention efforts toward more costly pathogens in order to minimize the financial impact of the disease on families. Additionally, the feasibility of controlling or eliminating diarrheal episodes differs depending on the causal pathogen. Estimating household costs by pathogen may help determine the full economic impact of diarrheal disease control efforts at a public health level, particularly those that are pathogen-specific, such as vaccines. In this study, we aimed to evaluate the household costs of diarrheal disease by pathogen in 7 countries.Cryptosporidium, ST-ETEC, and Shigella ..5].During the enrollment interview, the caregiver was asked about health care utilization for the diarrheal episode before the SHC visit. The caregiver estimated his/her total out-of-pocket expenses for the child’s medical care and transportation to health care providers, including pharmacies, traditional healers, unlicensed practitioners/village doctors/bush doctors, licensed practitioners/private doctors, shops or markets providing remedies and medicines, and other hospitals or health care centers. When the child was discharged from the SHC, the caregiver was asked about out-of-pocket expenses for care that the child received at the SHC, including costs for transportation to the hospital or clinic, consultations, drugs, diagnostics , food, or other costs. Caregivers were also asked about the origin of the money used to cover these expenses and earnings lost due to seeking or providing care during the child’s illness.We used a retrospective cohort design for this analysis, selecting only cases from the GEMS case–control study and performing a cohort analysis on the selection. We included any patient in our analysis with nonmissing cost data who was classified as an MSD case in GEMS and GEMS-1A and an LSD case in GEMS-1A.Cryptosporidium, ST-producing ETEC (ST only or LTST), Shigella, Campylobacter jejuni, norovirus GII, and Vibrio cholerae O1. We selected these pathogens due to their potential for treatment or prevention, hypothesized influence on costs, and/or prevalence. Pathogens common in other settings, for example, Salmonella or amebiasis, represented a small or nonexistent attributable fraction of diarrheal disease in this population and were therefore not included in this analysis.GEMS measured the presence of multiple pathogens . A priorThe outcome of interest was total costs to the household. To standardize cost data, we inflated all costs in local currency to the year 2012, the final year of enrollment. We then converted local currency in the year 2012 to 2012 US dollars (USD) using consumer price index data. To calculate total household costs, we summed all out-of-pocket costs due to the episode of diarrhea, both before and during the visit, including medical costs, transportation, and lost wages. We also included time costs for any reported work time missed for transportation or providing care. To include time costs, we summed all lost wage days and multiplied by the gross domestic product per capita in 2012 USD, divided by 240 working days per year. Finally, we included the costs of prescriptions given for treatment at home. Country-specific prescription costs were not available, so these costs were based on international estimates . The treWe examined baseline characteristics for the study population, including age, gender, loose stool characteristics, duration of disease before visit, and other symptoms. We then tabulated the presence of each of the 7 pathogens of interest in the study population. We also tabulated costs for inpatients and outpatients, separated by pathogen and country, and tabulated component costs for drugs, consultation fees, diagnostics, food, transportation, lost earnings, cost of the diarrheal episode before the study, and other costs, by pathogen and country. Costs before the study included any drugs, doctor visits, hospitalization, and transportation related to the diarrheal episode but incurred before study enrollment. Additionally, we compared the means and standard deviations of work time lost and of length of stay for patients with each pathogen in each country.To adjust for the presence of multiple pathogens, we used a 2-part model with a logit function for any costs, followed by a generalized linear model with gamma family and log link. If too few patients had 0 costs to calculate margins for the probability of any costs, we assumed the probability of having costs was 1 and used a generalized linear model alone. The model was adjusted for the 7 pathogens, age group, gender, and country. We ran the 2-part model overall, adjusting for country, and additionally ran the model for each country independently.Inpatient vs outpatient status and MSD vs LSD were mediating variables, so we did not adjust for them in the models described above. We did perform separate 2-part models to assess the effects of these 2 variables on cost by pathogen. We ran a 2-part model for MSD inpatients, MSD outpatients, and LSD patients . These models were adjusted for the 7 pathogens, age group, gender, and country. Dysentery (bloody diarrhea) and the days of diarrhea from onset before the visit were also considered mediators and were not included in the models. As a sensitivity analysis, we completed the 2-part model with measures of severity  included as confounders.We calculated 95% confidence intervals based on the product of 1.95 times the SD for each part of the 2-part model. We also analyzed the model using time costs as the outcome to assess the impact of pathogens on costs of time only.During the 36-month GEMS and 12-month GEMS-1A study periods, a total of 15 303 cases (9439 cases in GEMS and 5864 cases in GEMS-1A) were enrolled, of whom 12 071 MSD cases and 3157 LSD cases had cost data available and were included in this analysis. The characteristics of the study population are shown in Cryptosporidium (8.7%) were the most prevalent pathogens for LSD, and rotavirus (17.7%), Shigella (11.4%), and Cryptosporidium (11.2%) were the most prevalent pathogens for MSD.Detection of the 7 pathogens of interest is shown in The unadjusted average out-of-pocket costs per patient for each of the pathogens of interest are shown in Lost earnings costs were the highest component cost and were highest in Kenya and lowest in Mali and Pakistan . The nexAverage length of stay ranged from 2.0 (India) to 6.2  days, and lost work time ranged from 0.1  to 2.4 (Kenya) days . We obseVibrio cholerae O1. Household costs were highest in Kenya and Mali, ranging from $14.88 for Campylobacter jejuni to $17.87 for Cryptosporidium in Kenya and from $14.41 for norovirus GII to $22.25 for Campylobacter jejuni in Mali. Expected household out-of-pocket costs were lowest in The Gambia and Pakistan, ranging from $4.21 for Campylobacter jejuni to $6.29 for rotavirus in The Gambia and from $3.32 for Campylobacter jejuni to $6.31 for Vibrio cholerae OI in Pakistan. Results of regression models can be found in Expected adjusted total out-of-pocket costs for a patient with each pathogen in each country are shown in Within countries, household cost differences between pathogens were, for the most part, minimal and were within the 95% confidence intervals of each other, indicating nonsignificant differences between countries . Using tExpected adjusted total out-of-pocket costs for inpatient and outpatient MSD and LSD patients with each pathogen are shown in Among this population of children in 7 low- and middle-income countries, we found that unadjusted mean household costs of diarrheal disease by pathogen ranged from $8.19 for norovirus GII to $12.83 for rotavirus. Upon adjustment for presence of 6 other pathogens, country, age group, and gender, we found that household costs were higher in Kenya and Mali and lower in The Gambia and Pakistan. Within countries, expected household costs for each pathogen were within 95% confidence intervals of each other, indicating no significant difference in household costs by pathogen. We also found that household costs were highest for MSD inpatients followed by MSD outpatients, and costs were lowest for LSD patients. Although we did not compare costs for patients without the pathogens of interest, we would assume that those without pathogens causing severe disease would have lower costs. Some of the differences in household costs by country may be due to differences in overall costs and the distribution of costs between the health system and the household, but we are unable to conclusively identify the reason for these differences in this analysis. Overall, mean out-of-pocket costs are driven most by lost earnings. However, in Mali, drug costs and hospital costs are bigger drivers. In India and Pakistan, doctor and pharmacy costs before the study are also important drivers.All cases enrolled in GEMS belonged to a censused population at each study site. Health care costs for diarrheal disease were also estimated in these censused populations in preparation for the GEMS case–control study using a Healthcare Utilization and Attitudes Survey of a randomly selected sample of the censused population stratified according to the same age categories used for cases , 8. WhenThere are several limitations that may have prevented this analysis from differentiating costs by pathogen. First, our analysis was limited by the lack of cost data from the facility, meaning that we could examine only costs to the household, not the total cost of a diarrheal episode. There could be differences in the costs to the facility for providing different types or levels of care, which we were not able to examine in this analysis. Second, we are limited by costs incurred only before and during the visit to the health care facility. Additional costs related to diarrheal disease may have been incurred after the visit. Therefore, our estimates should not be used to understand the full economic burden of diarrheal disease and may differentially underestimate the burden of pathogens associated with longer illnesses. Third, we lacked country-specific prescription costs; therefore, we incorporated intercountry differences due to prescribing rates but not unit costs. Fourth, although we utilized sophisticated statistical techniques to differentiate costs by pathogen, numerous pathogens were present in stool samples, and we were unable to conclusively identify any single causal pathogen for a specific diarrhea episode, which may limit the variation in costs by pathogen. We also note that our data were collected approximately 10 years ago, meaning that the values in this analysis may no longer be accurate measures of household costs. This does not affect our ability to examine costs by pathogen, which is the main objective of this paper, but caution should be exercised if one were to consider these values relative to more recently collected data. Finally, we selected pathogens a priori that were likely to cause more severe disease. Although we did include both MSD and LSD cases, we likely did not see as much variation in disease severity as we would have if all pathogens had been included. Although this may have limited our ability to detect cost differences between other pathogens, our goal was to assess meaningful differences between pathogens of interest, not to examine all potential pathogens.Despite these limitations, an understanding of pathogen-specific differences in household costs (or lack thereof) is useful, as decision-makers could consider broader illness cost information and its relevance to a particular pathogen’s economic burden and contribution to poverty when deciding which pathogens to target with vaccines, drugs, or other pathogen-specific interventions. This study suggests that hospitalization is a key driver of diarrheal costs, though we did not identify significant differences by pathogen, because management of diarrhea tends to consist of rehydration and antibiotics. Our finding of considerable household costs for diverse diarrheal pathogens also highlights the importance of integrated intervention approaches that help address many diarrheal pathogens, such as nutrition and improvements in water, sanitation, and hygiene alongside vaccines.


Frontal analysis continuous capillary electrophoresis (FACCE) was successfully applied to determine binding constants and binding stoichiometries. The effect of DGL generation on the interaction was evaluated for the first three generations  at different ionic strengths, and the effect of ligand topology (linear PLL vs. dendrigraft DGL) on binding parameters was evaluated. An increase of the biding site constants accompanied with a decrease of the DGL-PAMAMPS (n:1) stoichiometry was observed for increasing DGL generation. The logarithm of the global binding constants decreased linearly with the logarithm of the ionic strength. This double logarithmic representation allowed determining the extent of counter-ions released from the association of DGL molecules onto one PAMAMPS chain that was compared to the total entropic reservoir constituted by the total number of condensed counter-ions before the association.In this present work, three generations of dendrigraft poly( Dendrimers are nano-sized, radially symmetrical molecules with well-defined and monodisperse structure consisting of tree-like arms or branches . Due to 5 M−1 for G0 to 5.42 × 106 M−1 for G6) followed by a slight decrease for G8 dendrimer (3.3 × 106 M−1). This study showed that binding constants depended on the chemical structure of the core and the terminal group of dendrimers. Furthermore, DNA-PAMAM dendrimer complex stability and binding constant were found to increase with dendrimer generation  for different initial molar ratio [DGL]0/[PAMAMPS]0. The stoichiometry of interaction n expressed in term of bound DGL entities per PAMAMPS chain and the binding site constant k were determined by non-linear least square routine on Microsoft excel using the model of identical interacting sites [It is obvious that the interactions between DGL and PAMAMPS are expected to be highly dependent on the DGL generation and very different compared to poly(ractions ) becauseractions  was usedng sites  expresseDGL]0 and [DGL] are the initial and free ligand concentrations, respectively. [PAMAMPS]0 is the concentration of PAMAMPS initially introduced in the mixture. It is worth noting that the intrinsic binding constant k refers to the association of one ligand (one DGL molecule) onto a binding site –s corresponding to a small portion of PAMAMPS: DGL] and [DGL− s] are the free and complexed DGL concentrations at equilibrium respectively, [− s] is the concentration of free sites. An example of isotherm of adsorption for the interaction G3-PAMAMPS 30% at 552 mM ionic strength is given in I for each DGL generation and for two PAMAMPS chemical charge density (30% and 100%). However, accurate measurements of the binding parameters by FACCE required the adjustment of the ionic strengths to avoid unmeasurable high binding constants at low ionic strength, or low affinities due to the dissociation of PEC at high ionic strength. For that, the ionic strength of recomplexation Irecomp  was first determined by turbidimetry, as previously described [Irecomp according to the molar masses of the purified DGL in double logarithmic scale. As can be seen in n and k were measured in a range of ionic strength from 40% to 90% of Irecomp  yielding measurable binding site constants k between 1.6 × 104 M−1 and 7.7 × 106 M−1.In order to get the ionic strength dependence of the binding constants and stoichiometries, isotherms of adsorption were determined at different ionic strengths escribed . Figure nDGL/PAMAMPS) is presented in nDGL/PAMAMPS) [The stoichiometry of interactions -lysine) . n(Lys/AMPS)) is given in n(Lys/AMPS) is higher than one whatever the DGL generation number, and also for PLL 50. This is in good agreement with the general rule recently enounced [n(Lys/AMPS) > 1). DGL G2 and the linear PLL50 (DP 50) have almost the same molar masses . It is thus interesting to consider the effect of the ramification on the PEC stoichiometry at comparable molar masses. Interestingly, the charge stoichiometry was, in average, slightly lower for DGL G2 (1.31) than for PLL50 (1.56), as if the charge parameter of DGL G2 was lower than for PLL50. On the other hand, for DGL G3 and G4, the n(Lys/AMPS) stoichiometry was higher than for PLL50, as if the DGL G3 and G4 were more charged compared to PLL50. Even if the charge parameter is hardly accessible for the DGL, or even not well-defined, one can compare the counter-ion condensation rates θ+ that were previously determined by isotachophoresis [The charge stoichiometry expressed in terms of lysine residues per AMPS monomers (enounced  stating n(Lys/AMPS) = 0.99). In the case of the DGL/PAMAMPS 100%, the n(Lys/AMPS) stoichiometry seems to be higher than one, and seems to increase with the increase in generation number, as if the charge density (or charge parameter) of the DGL increased with the DGL generation and becomes higher than the PAMAMPS 100% linear charge density. Again, these results correlate well with the increase of the counter-ion condensation with the DGL generation, i.e., an increase of the charge parameter with the DGL generation.As for the PLL50/PAMAMPS 100% interaction, the polyanion is the highest charged polyelectrolyte and it is introduced in default at saturation of the isotherm. In that case, the rule states that the charge stoichiometry tends to 1 , as obsek represents the equilibrium constant relative to the interaction between one DGL molecule (one ligand) with one interacting site –s of a PAMAMPS chain (substrate). This interacting site –s is defined as a fragment of PAMAMPS chain carrying electrostatic anchoring AMPS monomers. The variation of binding site constants k with the ionic strength is represented in k decreased linearly with log I. Moreover, for a given ionic strength, the higher the generation is, the higher the binding constant is, for both DGL-PAMAMPS 30% and DGL-PAMAMPS 100% systems. This increase of binding site constant can be qualitatively explained by the increase of the number of possible electrostatic anchoring points on each ligand, which grows exponentially with increasing DGL generation number. According to the model of identical interacting sites previously described for the study of PLL/PAMAMPS interactions ,42, the nβ, representing the equilibrium associated to the full binding of the n sites of the substrate [The global binding constant ubstrate  is relatnβ was found to decrease linearly with the ionic strength of the medium . It can be seen from As observed for PLL/PAMAMPS systems ,42,43 andium see  with an n ligands onto one PAMAMPS chain can be determined by calculating DP of one binding site on the PAMAMPS 30% chain increased from 128 to 160 when going from linear PLL (DP = 50) to DGL 2nd generation, G2 (DPn = 48), and increased with increasing DGL generation, 265 for G3 (DPn = 123) and 750 for G4 (DPn = 365). It clearly illustrates the steric constraints for the PAMAMPS chain to access the core of the DGL, especially for higher generations. Thus, despite the increase of the total number of condensed counter-ions before the association (Ncounter-ions) given in Ncounter-ions was estimated via the Manning condensation theory. Therefore, we did not consider here the possible variation of the number of condensed counter-ions according to the ionic strength. This topic is still discussed as some authors reported a decrease of the fraction of condensed counter-ions with an increase of the ionic strength using numerical simulations [The number of counter-ions that are effectively released from the association of ogk∂logI ,42,43. Tulations , while oulations .l-Lysine) interacting with linear PAMAMPS. The influence of the ligand topology and the ionic strength on the interactions was studied. At a given ionic strength, it was found that higher DGL generations led to stronger binding site constants. DGL-PAMAMPS (n:1) stoichiometries decreased with the increase in DGL generation number and were almost independent of the ionic strength. Furthermore, a double logarithmic linear dependence between the global biding constants and the ionic strength was observed. The slope of each line is a direct experimental estimation of the number of released counter-ions from the association of n DGL molecules onto PAMAMPS chains. Surprisingly, the number of released counter-ions decreased with increasing generation number. This result was far from being intuitive since the entropic reservoir, corresponding to the number of initially condensed counter-ions, increases with increasing DGL generation. The fact that only a small proportion of the initially condensed counter-ions are released can be explained by a low accessibility of the PAMAMPS chain to the core of the DGL.FACCE method was applied to determine the binding parameters between linear and dendrigraft poly(


Journal of Inherited Metabolic Disease discusses highlights of the International GSD conference held at the University Medical Center Groningen, the Netherlands, between 15 and 17 June 2017 (IGSD2017). Fifty-three oral presentations, 52 posters, 11 networking sessions, and 2 “Meet the Expert” sessions attended by 406 participants from 36 countries reflected the recent progress in individualized and novel therapies, monitoring, and empowerment for patients with muscle- and/or liver-specific GSD types.The glycogen storage diseases (GSD) are amongst the earliest recognized inborn errors of metabolism. After the Fulda Workshop on Glycogen Storage Disease (GSD) type I in 1990, international GSD conferences have been held in Fulda (2000), Milan (2010), Lyon (2012), and Heidelberg (2013). Since the start of the internet era, parent-led patient organizations have pushed for international guidelines for treatment and follow-up Phillips . Subsequhttp://igsdpsp.com) was initiated during the IGSD2017 conference, in collaboration with the James Lind Alliance (http://www.jla.nihr.ac.uk/). This partnership aims to identify and prioritize research addressing current uncertainties about the effects of care and management. The IGSD-PSP is the first international, multi-lingual PSP for a group of ultra-rare disorders. The steering group expects to present the results at the end of 2019.To foster the involvement of all stakeholders, including parents, in setting the future research agenda, the International Liver Glycogen Storage Disease Priority Setting Partnership (IGSD-PSP)  dietary management after a single dose of gene therapy. To date, longitudinal, in vivo functional studies of glucose metabolism in animal models after gene therapy are lacking. Case histories of “mild” GSD Ia patients have demonstrated that episodes of hypoglycemia can remain undiagnosed until patients present with liver adenomas, indirectly emphasizing the importance of determining that exogenously administered genes are stably expressed. Longitudinal monitoring of GSD Ia patients after gene therapy may include a combination of (1) assessment of microsomal glucose-6-phosphatase activities ex vivo (necessitating invasive liver biopsies), (2) execution of  fasting challenges in vivo, (3) advanced continuous glucose monitoring in the home situation, and (4) application of stable isotope methods to longitudinally quantify endogenous glucose production rates in vivo (van Dijk et al. We are delighted to present this special collection of papers about GSD. Ultra-rare inborn errors of metabolism do not stop at borders between countries or continents and global collaborations are essential. Clinical expertise, secure eHealth applications, active patient participation, and transparent governance structures including all important stakeholders will be fundamental to improving cross border transfer of knowledge, care, and cure between professionals and patients, in all possible directions.


Beauveria bassiana  Vuillemin (Cordycipitaceae) is the main candidate to explore this pathway since it has a major number of shared genes with other non-fungal pathogens that infect orally, such as Bacillus thuringiensis Berliner . This finding gives B. bassiana a potential advantage over other entomopathogenic fungi: the possibility to infect through both routes, oral and cuticular. In this review, we explore all known entry gates for entomopathogenic fungi, with emphasis on the infection per os. We also set out the fungal infection process in a more integral approach, as a need to exploit its full potential for insect control, considering all of its virulence factors and the conditions needed to improve its virulence against insect that might offer some resistance to the common infection through the cuticle.Entomopathogenic fungi are the only insect pathogens able to infect their host by adhesion to the surface and penetration through the cuticle. Although the possibility of fungal infection per os was described almost a century ago, there is an information gap of several decades regarding this topic, which was poorly explored due to the continuous elucidation of cuticular infection processes that lead to insect death by mycosis. Recently, with the advent of next-generation sequencing technologies, the genomes of the main entomopathogenic fungi became available, and many fungal genes potentially useful for oral infection were described. Among the entomopathogenic Hypocreales that have been sequenced,  Beauveria bassiana s.l. and Metarhizium anisopliae s.l. [Over the last 400 million years, fungi and insects have coexisted, developing interactions in different ways ,2. Amongiae s.l. ,4. The miae s.l. . Once iniae s.l. . B. bassiana [Metarhizium spp. [B. bassiana became available in the context of insect-pathogen coevolutionary studies [B. bassiana  a harder challenge to the insect’s immune system, thereby a good candidate to optimize sustainable and ecofriendly alternatives to chemical pesticides. In the following sections, we present information about all known routes of entry for hypocrealean entomopathogenic fungi, with emphasis in the least explored, per os, insect infection route. Infection by ingestion is a rare route for entomopathogenic fungi, but quite common for other pathogens such as protozoa, bacteria, and viruses, which display a series of virulence factors that allow them to be ingested and thus infect from the oral cavity and/or intestinal tract . A distibassiana  and Metaium spp. ,9 has al studies . Thus, tMad1, Mad2) and hydrophobins or hydrophobin-like proteins  [CYP) involved in insect hydrocarbon degradation was described long ago for B. bassiana [B. bassiana (CYP52X1) [M. robertsii (CYP52X2) [Chit1, Chit2, Chit3, Chit4, and subtilisin, trypsin, and cysteine proteases  [The first contact that an entomopathogenic fungus makes with its host is achieved by nonspecific hydrophobic and electrostatic interactions between conidia and the insect cuticle; some species even produce a mucus substance that helps fungal adhesion . As was , Cwp10)   . A suitebassiana , and somCYP52X1)  and M. rCYP52X2) . Immediar2, Pr4) —that actr2, Pr4) ,18. Furtr2, Pr4) ,20. Bothr2, Pr4) .Mos1) or encoding for a defensive coating protein (Mcl1), which help hyphal bodies to resist the hard environment found in the hemolymph. Furthermore, antioxidant systems are triggered to mitigate reactive oxygen and nitrogen species (ROS and RNS) released by the host [Nrr1, Crr1, Mest1, Atm1, and Gat, among others [Beauveria bassiana produces secondary metabolites acting as immunosuppressants, facilitating infection, such as beauvericin (Bea), bassianolide (Bsl), oosporein (Op), tenellin (Ten), bassiantin, and beauverolides [Metarhizium spp. produce mainly destruxins (Dtx) [Once the cuticle is breached, the pathogen reaches the hemolymph, where it needs to adapt to the new environment while it continues to fight against insect immune system  Figure . The funthe host ,12,21. Eg others . Beauvererolides , whereasns (Dtx) ,12  . Insect infection by microbial ingestion is the rule when the pathogen is a virus, bacteria, or protozoa; however, it has also been proposed that entomopathogenic fungi can use oral and respiratory routes as an alternative to the cuticle penetration for entrance to the host ,24,25,26B. bassiana could invade the oral cavity of pine weevils. From the mid-1940s to the mid-1980s, a discontinued series of research started to gaze into the alternative ways that a fungal pathogen had to colonize its host; the presence of M. anisopliae hyphae around the implantation of the mandibles and esophagus of Ephestia kuhniella Zeller  [M. anisopliae from the gut of Oryctes larvae were documented [Schistocerca gregaria Forskål (Orthoptera: Acrididae) with M. anisopliae-infected leaves to test oral infection, disinfecting the insect heads to prevent cuticular infection. This research showed that fungal hyphae were present only in the maxillary palps and head, but not in other parts of the body [Studies on the possibilities of oral/intestinal infection by entomopathogenic fungi have been of interest for many years, and yet, there is much to elucidate on how these routes work. Almost 100 years ago, Peirson  hypothesralidae) ,36 and rcumented . Veen [3cumented  fed secothe body . Hylobius pales Herbst (Coleoptera: Curculionidae), was reported by Schabel [M. anisopliae conidia, then conidia viability was determined, and histological analyses of the insect gut were carried out. High mortality was achieved, and hyphae growth was observed in all portions of the digestive tube; however, no clear evidence of germination in the gut was observed, suggesting that fungal conidia invade through the beetle mouthparts [S. gregaria fed with M. anisopliae conidia produced similar results, reinforcing the hypothesis that rather than penetrating the gut, which is protected by its microbiota, fungal conidia adhere to, germinate on, and penetrate through the buccal apparatus to kill the insects [Leptinotarsa decemlineata Say (Coleoptera: Chrysomelidae), was also fed with fungal conidia, but in this case, B. bassiana was used, as reported by Allee et al. [Bombyx mori exhibited midgut cells dissolved by fungal metabolites and hyphae growing from the midgut out [Sitophilus granarius Linnaeus (Coleoptera: Curculionidae) fed with a mixture of conidia and diatomaceous earth, where insects cuticles were disinfected to prevent cuticular breaching, showed that ingested conidia of B. bassiana and M. anisopliae were able to infect the digestive tube and kill the beetle [A very thorough study to evaluate the oral infection of pine weevil,  Schabel . The insuthparts . Further insects ,39. The e et al. ; germinae et al. . In contdgut out . A more e beetle . NeverthThis suite of studies on terrestrial insects showed that the mechanisms that ingested spores use to kill the host are not very clear. In some cases, it appears that fungal spores would adhere to parts of the buccal cavity more than the digestive tract, since no germination of conidia has been detected in the gut. Further information and careful experimental design are needed to shed some light on physiological and molecular changes when entomopathogenic fungal spores are ingested. M. anisopliae float in water since they have a hydrophobic surface. Thus, when the larvae open their perispiracular valves for air intake, conidia reach the surface of the insect and attach at the syphon tip; then, hyphae grow into the trachea and can kill the insect by suffocation [Mosquito larvae, which grow in an aquatic environment, seem to offer some choices for infection by entomopathogenic fungi adapted to terrestrial hosts. However, the species have not evolved to interact, and although fungi retain pre-formed pathogenic determinants that mediate host mortality, they do not recognize and colonize their host as true aquatic fungal pathogens do . The confocation . If the focation . Culex spp. and Anopheles spp. do not harm conidial viability upon passage through the digestive tract [M. anisopliae conidia within the gut of S. gregaria showed fungitoxicity dependent on the gut flora [Aedes aegypti Linnaeus (Diptera: Culicidae), the two primary infection sites were the head and the anal region when fed with B. bassiana conidia; nevertheless, the most preferred site for fungal development was the larval gut [Dietary stress is thought to have a big impact in this last route of entry since conidia represent indigestible material for larvae and occupy the digestive tract, limiting the host’s access to ingested nutrients . Reportsve tract , but M. ut flora . For Aedrval gut . Regardirval gut  demonstrCulicinomyces spp., that infects aquatic larvae of culicid dipterans has the ability to adhere and to colonize the insect by adhesion to the anal papillae and not to the cuticle [Culicinomyces clavisporus Couch, Romney & Rao , and Culicinomyces bisporalis Sigler, Frances & Panter , on larvae, eggs, and adults of A. aegypti, including transstadial transmission. They also found that after repeated serial repassages through A. aegypti larvae, C. clavisporus killed faster and with a lower dose, although it was not clear whether the repassages improved the virulence or might have restored some of the original insecticidal activity [A very peculiar entomopathogenic fungus,  cuticle ,47. To a cuticle . Rodrigu cuticle  reportedactivity .Bacillus thuringiensis, include in their genomes a battery of virulence factors that allow them to invade the insect and kill it from the gut [B. bassiana has at least 13 heat-labile bacteria-like enterotoxins compared to six in M. robertsii and one or none in the rest of the entomopathogenic fungi; additionally, B. bassiana also has eight Cry-like delta enterotoxins and three bacteria-like zeta toxins proteins, whereas other entomopathogenic fungi have one or none, suggesting that B. bassiana would have a greater oral toxicity than other entomopathogenic fungi [The acquisition of massive data through genomics and transcriptomics, mostly in the last decade, uncovered much valuable information for starting to understand the complex molecular mechanisms underlying these host-pathogen relationships. Pathogens that traditionally invade the host through ingestion such as the entomopathogenic bacterium,  the gut . By mini the gut ,8,9  through conidial ingestion; the authors observed that the engineered strain was significantly more virulent than the wild type, but virulence was not modified when infection occurred via the cuticular route [B. bassiana to red flour beetle Tribolium castaneum Herbst (Coleoptera: Tenebrionidae) resulted in infections, but showed no differences in the activation of the prophenol oxidase pathway, which is activated when the fungal pathogen penetrates through the insect cuticle [T. castaneum may be the reason why it was difficult to explain evolved and acquired resistance to B. bassiana since it would be able to infect through both cuticular and oral routes [T. castaneum cross-resistance coevolved between B. thuringiensis and B. bassiana [B. bassiana genome contains Cry-like toxins similar to those found in B. thuringiensis, both pathogens may share mechanisms of infection such as oral toxicity [By genetic manipulation, the vegetative insecticidal protein Vip3A from ar route . In a co cuticle . Evidencl routes . It was bassiana . Thus, stoxicity .Biocontrol of insect pest and vectors has been a safe and eco-friendly alternative to chemical insecticides around the world . EntomopMetarhizium spp. is not able to germinate in the host gut. Many factors may influence per os infection, among which conidia must be viable and germinate in the gut conditions  and must also have sufficient contact time with the gut wall to allow germination and penetration [B. bassiana has potential over other fungi to display greater oral toxicity based on the several genes involved in virulence by oral infection that it shares with bacterial pathogens [B. bassiana, which seems to be the most suitable candidate to act through both cuticular and oral infection routes.Most past studies lacked an optimal experimental design in order to eliminate the possibilities of contamination and infection by cuticle attachment; but successful experiments have demonstrated that even if ingested, etration . Host deathogens . This to


We investigated the role of service delivery modalities and the link between facility-level management practices and unit cost variability along both services’ cascades.Like most countries with a substantial HIV burden, Nigeria continues to face challenges in reaching coverage targets of HIV services. A fundamental problem is stagnated funding in recent years. Improving efficiency is therefore paramount to effectively scale-up HIV services. In this study, we estimated the facility-level average costs , input prices, and output data for the year 2013. Staff costs were adjusted using time-motion methods. We estimated the facility-level average cost per service along the HCT and PMTCT service cascades and analyzed their composition and variability. Through linear regressions analysis, we identified aspects of service delivery and management practices associated with unit costs variations.The weighted average cost per HIV-positive client diagnosed through HCT services was US$130. The weighted average cost per HIV-positive woman on prophylaxis in PMTCT services was US$858. These weighted values are estimates of nationally representative unit costs in Nigeria. For HCT, the facility-level unit costs per client tested and per HIV-positive client diagnosed were US$30 and US$1,364, respectively; and the median unit costs were US$17 and US$245 respectively. For PMTCT, the facility-level unit costs per woman tested, per HIV-positive woman diagnosed, and per HIV-positive woman on prophylaxis were US$46, US$2,932, and US$3,647, respectively, and the median unit costs were US$24, US$1,013 and US$1,448, respectively. Variability in costs across facilities was principally explained by the number of patients, integration of HIV services, task shifting, and the level of care.Our findings demonstrate variability in unit costs across facilities. We found evidence consistent with economies of scale and scope, and efficiency gains in facilities implementing task-shifting. Our results could inform program design by suggesting ways to improve resource allocation and efficiently scale-up the HIV response in Nigeria. Some of our findings might also be relevant for other settings. To address the continued HIV burden the Nigerian government rolled out the 2010–2015 HIV/AIDS Strategic Plan and aimed to achieve 80% coverage of two primary pillars of the HIV response .Funding is a crucial constraint for Nigeria to expand and sustain the provision of HIV services. As other countries with generalized epidemics and high HIV prevalence, funding to support HIV programming relies heavily on international donors and has plateaued in recent years ,5. ThereThe Nigerian government has identified potential mechanisms to improve efficiency and increase access to HIV services. Among them are, decentralizing services from secondary and tertiary facilities to primary care clinics, integrating HCT services into routine health services, expanding demand generation activities, increasing task-shifting, and strengthening community mobilization . HoweverAnalyzing the costs of HIV services could help to identify the links between these approaches and efficiency, and to determine their relative importance. While previous costing studies have been conducted on HIV services in Nigeria, they have been limited in their scope, focusing solely on estimating the unit cost of services (the average cost per service delivered). However, in addition to assessing the unit cost of HIV services, identifying the determinants of unit cost variation can illuminate potential pathways to improve the performance of service delivery.In this study, we applied micro-costing methods to a large and partially representative sample of facilities to assess costs and the determinants of cost variation of HCT and PMTCT services in Nigeria. In particular, we were interested in studying two aspects of service delivery and their association with efficiency. First, we explored the relationship between unit costs and service delivery models including the level of care , integration of HIV services , task-shifting, and community involvement. Second, we explored the association between management practices and efficiency.This study is part of a broader project, Optimizing the Response to Prevention and Treatment: HIV Efficiency in Nigeria (ORPTHEN). The objective of the study was to estimate and analyze average costs per services at the facility-level for the following HIV interventions: HIV counseling and testing (HCT), prevention of mother-to-child transmission (PMTCT), and antiretroviral treatment (ART) . This paFor this study, we adapted to Nigeria the methods from a cross-sectional, micro-costing study conducted previously in four other African countries. Those methods have been described elsewhere . Below wWe applied multistage sampling first to select the 20 states with the highest HIV prevalence—we excluded three states due to security reasons—and subsequently to randomly sample facilities that provided at least one of the two interventions of interest (HCT or PMTCT). All levels of care  were represented. Facilities were mostly integrated sites (offering both HCT and PMTCT services). At the time of data collection, 198 and 194 facilities in the sample provided HCT and PMTCT services, respectively; and they included teaching and referral hospitals, health centers, and maternal health clinics. HCT services in these facilities included both client-initiated and provider-initiated rapid HIV test algorithms (immunochromatographic assays). PMTCT services included HCT, routine clinical monitoring, and provision of ART and other drugs to pregnant women, mothers, and infants through Options A, B, and B+ .Due to incomplete or missing information on outputs or staff composition, we excluded 46 HCT facilities and 43 PMTCT facilities from the sample. We eliminated an additional 11 HCT and 14 PMTCT facilities due to implausibly low or high unit costs. The final analytical sample includes 141 facilities offering HCT and 137 facilities providing PMTCT services  require time to build demand for their services. On the other hand, HCT or PMTCT services with fewer than 0.5 clients per day per provider and more than one year providing those services were unlikely to be real or stable, and their inclusion in the sample could bias the results.Given the relatively large proportion of excluded facilities, we performed an attrition analysis to assess the possible bias introduced by sample loss. We compared the subset of facilities excluded with those in the final analytical sample in terms of state, type of facility, level of care, total costs, total input costs, and total FTE. We present the results in Data collection took place between December 2014 and May 2015. Data on inputs, input prices, outputs, process quality, the competence of providers, staff’s time allocation, and facility characteristics—including management practices—were collected retrospectively from databases at the facility and district levels, program records, and monthly reports from the year 2013. Data were collected over two- to four-day time periods using standardized, pre-programmed, computer-based instruments by teams consisting of three trained surveyors. Facility-level questionnaires were administered to the facility’s manager in charge, consulting and validating the information on logs and records as much as possible. We collected data on input prices at the national level from the Ministry of Health. We also implemented a data quality assurance system which provided a mechanism for the research team to download the data on a weekly basis to assess completeness and quality of data .We captured information on inputs used to produce HCT and PMTCT services. Namely personnel, recurrent inputs and services, capital . Individual incentives summarize the different types of monetary, non-monetary and other in-kind incentives that staff can receive for individual-level good performance. Providing financial incentives for performance has been shown to impact the quantity and quality of services offered [sanctions index measures the types of sanctions used to penalize poor individual performance. The external supervision index measures the amount of oversight received by the clinics. While excessive monitoring may negatively affect a facility’s ability to react swiftly to its needs and find solutions, external supervision may improve aspects of service delivery by providing staff guidance and feedback on performance. The transparency index measures the amount of information dissemination in which the clinic engages. Transparency may lead to less waste and more efficient use of resources, and can influence efficiency directly. The community participation index score measures how involved the community is in decision-making processes at the clinic (e.g. in the governing board) or in activities carried out by the clinics; facilities with more community involvement may be more effective at targeting services, engaging risk populations and retaining patients, thus influencing efficiency [National Governance and Community Governance indices measure the amount of involvement that the national government and community entities have over budgetary decisions, respectively. More oversight and support may lead to improved efficiency through better planning and more appropriate use of resources, or could cause more bureaucracy. offered . On the  offered . However offered . The sanficiency . The Natth percentile, and for the remaining variables, we used the median. For each category of management, we constructed an index using additive scores. Their internal consistency was assessed using Cronbach’s alpha . We further validated the management indices by applying Principal Component Analysis (PCA) to all variables used in the six scores. We included eight variable scores in the models as binary variables for ease of interpretability. We defined the cut-off points according to their distribution: for performance-based funding and financial decisions by the community, we used the 75We measured other facility-level characteristics to investigate their associations with unit costs variations. We estimated the total annual costs for each intervention applying a micro-costing approach from the perspective of service providers. Using quantities and prices of essential inputs as well as output data for both the HCT and PMTCT service cascades, we computed facility-level total costs by intervention, as follows:TCjk denotes the total annual cost of intervention j  at facility k. The term ICijk denotes the annual cost of input category i , for intervention j at facility k.Where We estimated the average cost per service per facility-intervention (or unit cost) for each step of the service cascade, as follows:l, per intervention j, at facility k. TCjk indicates the total cost for intervention j at facility k; qjkl denotes outputs along the cascade where l = 1 for clients tested, l = 2 for clients tested and HIV-positive, l = 3 for HIV-positive clients receiving ARV prophylaxis or treatment, and l = 4 for infants born to HIV-positive clients receiving NVP, with the latter two only defined for PMTCT. Given attrition along the service cascades, qj11 ≥ qj12 for HCT and qj21 ≥ qj22 ≥ qj23 ≥ qj24 for PMTCT.Where For facilities providing more than one intervention, we apportioned shared inputs according to their contribution to total costs. Specifically, we weighted each category of shared input’s annual costs by the annual number of clients per intervention over the total yearly amount of outpatient clients in the facility. Finally, to allocate personnel costs across interventions, we applied weights derived from the time-motion study.All cost data were converted from local currencies to United States Dollars (US$) using the daily mean exchange rate for the year 2013 (Nigeria: 150 Nigerian Naira–NGN). We report both unadjusted costs and costs adjusted for purchasing power parity (PPP) for non-tradable services, primarily staff salaries.While the variation of unit costs across facilities is the focus of the analysis in this paper, we also estimated weighted unit costs, which are better estimates of the national-level average costs per service, than the mean of facility unit costs. To determine the weighted unit costs, we take into account the relative contribution of services provided by each facility. We calculated the weighted unit cost as the sum of each facility-level unit cost multiplied by a non-negative weight. We defined the weight as the ratio between the number of annual clients in each facility and the total number of clients in the full sample, for each step in the cascade, as follows:WUCjl denotes the weighted unit cost per output l, per intervention j. l, per intervention j, at facility k, summed from facility 1 to n. OPijk denotes the total number of clients per output l, per intervention j, at facility k, andWhere First, we describe the unit cost per service along the cascade and the average composition of total costs, by input categories and level of care. Second, we show the dispersion of unit costs across facilities along the service cascades, by level of care. Third, we present the correlation between unit costs and scale, measured by the annual number of services provided.We studied the efficiency of HIV services in Nigeria by analyzing the determinants of unit cost variation. We apply ordinary least squares (OLS) regression models, with robust standard errors to account for heteroskedasticity, as a function of outputs, facility-level characteristics, and the management indices, as follows:UCijk denotes the unit cost per output i, per intervention j, in facility k–with HCT (j = 1) and PMTCT (j = 2); and i = 1 for clients tested, i = 2 for HIV-positive clients identified, i = 3 for HIV-positive clients receiving ARV treatment or prophylaxis, and i = 4 for infants born to HIV-positive clients receiving NVP, with the latter two defined only for PMTCT.Where qijk is the number of annual output i from intervention j, at facility k; mjk measures the number of years since facilities began providing the intervention j (maturity) in facility k; ek is the average number of years of staff experience providing HIV services in facility k; lck indicates the level of care of facility k; cjk is the average competence score for intervention j in facility k; tsjk is a binary variable indicating whether task shifting is used in providing the intervention j in facility k. As a measure of integration of HIV services we included two additional variables; HIVjk measures the annual number of clients of intervention j in facility k ; and ARTk, a binary variable indicating whether the facility provided antiretroviral therapy (ART) or not. Finally, X is the vector of management indicators.On the right hand-side of the equation, The study was approved by the ethical review boards of the National Institute of Public Health, Mexico and the Nigerian Institute for Medical Research (NIMR).The average unit cost per HCT client tested was US$30, while the average unit cost per HIV-positive client was US$1,364. The equivalent figures in PMTCT services were US$46 and US$2,932, respectively. Average and median costs per unit of output varied substantially in both interventions, which implies a significant variation in unit costs across facilities.We further explored the composition of PMTCT and HCT costs in Nigeria. Regarding PMTCT services (Panel B), the staff category accounted by two-thirds of the total costs (65%), followed by HIV test kits (10%), capital costs (10%), antiretroviral drugs (8%), training (5%), and utilities (2%). The distribution was not significantly different across levels of care, except for the primary level, where staff represents a larger share of the total costs (76%).In panels C and D, we further break down the staff category into four cadre classes: doctors, nurses, other health staff , and indirect staff . Other health staff accounted for roughly 50% of the total staff costs in HCT, followed by nurses (30%), doctors (10%) and indirect staff (10%). In PMTCT, other health staff and nurses accounted for 46% and 42%, respectively, doctors 7%, and indirect staff 5%.In The unit costs of PMTCT services also varied considerably among facilities with differences of two and three orders of magnitude for the same service across facilities see . In the The volume of services is a critical factor in determining the efficiency of HCT and PMTCT services. We also found a negative correlation between the volume of PMTCT clients per facility and unit costs see . About 5We explored determinants of unit cost variation, including scale, scope, task-shifting, and managerial practices. unit costs in both steps of the cascade, which is consistent with economies of scale. The square term of the number of HCT clients was positive and significant, which indicates a decreasing rate of economies of scale. The level of service provision was not significantly associated with unit costs once we controlled for other characteristics—except for the unit cost per client tested at the tertiary level. We observed an association between task-shifting and lower unit costs in both steps of the cascade.As shown in Regarding management characteristics, we found associations between external supervision and the involvement of the government in financial decisions, with higher unit costs per person tested. Providing individual incentives was negatively associated with HCT unit costs. Finally, we found that everything else being equal, unit costs of HCT services were lower in facilities that also provided ART services (a measure of integration of services).As shown in Regarding management, we found an association between involvement of the government in financial decisions and higher costs per PMTCT client. Performance-based funding was associated with higher unit costs, although this relationship was statistically significant only in the first step. We observed a negative association between PMTCT unit costs and individual incentives and community involvement. Similar to HCT, facilities with ART services showed lower unit costs of PMTCT services. Finally, we found a positive correlation between competence and PMTCT unit costs .In a large and representative sample of facilities in Nigeria, we estimated the costs of HCT and PMTCT services cascades in Nigeria. The weighted average cost per HIV-positive client diagnosed in HCT services was US$130. The weighted average cost per HIV-positive woman on prophylaxis in PMTCT services was US$858. Weighted unit costs are estimates of the nationally representative costs in Nigeria given that we compute them accounting for each facility’s contribution to the national average based on their volume of patients. The estimated facility-level unit cost per client tested and per HIV-positive client diagnosed were US$30 and US$1,364 for HCT and US$46 and US$2,932 for PMTCT, respectively. The analysis on the composition of costs revealed that for both HCT and PMTCT services, costs are mainly driven by staff followed by HIV tests and ARV drugs, the latter only in the case of PMTCT. We found that the composition of costs was similar across levels of care. Other health staff and nurses categories accounted for the highest proportion of staff costs for both HCT and PMTCT.Unit costs increase along the cascade of HCT and PMTCT services, which is directly determined by two factors: positivity rates and attrition rates. For example, in the case of PMTCT, the gap between the cost per woman tested and the cost per HIV-positive woman diagnosed depends on the number of women that must be tested to find one HIV-positive case; lower positivity rates determine a higher cost per HIV-positive case. The gap between the cost per HIV-positive woman diagnosed and the cost per woman on ARV prophylaxis or treatment is determined by the proportion of women lost between these two steps in the cascade; a larger gap indicates more women lost proportionally. Our results suggest that secondary level facilities have more attrition than primary and tertiary ones, which may be an aspect of service delivery worth exploring in future studies.We also found variation in unit costs across levels of care. In the case of HCT services, the unit cost per HIV-positive client diagnosed decreases as the level of care increases. In PMTCT services, unit costs are higher among secondary level facilities than primary and tertiary, which is explained by HIV positivity rates in these facilities.The results of this study demonstrate variation in unit costs across facilities; we found differences of three to four orders of magnitude in costs for the same services across levels of care and along the service cascades. A large proportion of this variation was explained by scale, particularly in the first step of both cascades.However, even after controlling for scale, a substantial level of heterogeneity in unit costs persisted. Overall, we found that efficiency was linked to service delivery characteristics and management practices. At the national level, we observed evidence of economies of scope. We found that integration of HIV services, measured by the number of PMTCT or HCT clients tested and by the presence of ART services, seemed to be efficient. Facilities providing integrated HCT and PMTCT services, or ART services, were less costly. We also found evidence that task-shifting consistently predicts lower unit costs across the service cascades of both interventions. At the facility level, we found statistically significant associations between unit costs and management practices. Government involvement in financial decisions, external supervision, and performance-based funding, were practices associated with higher costs, whereas individual incentives and community involvement were associated with lower unit costs. Quality , and ownership. And these results hold for both interventions, suggesting that our main findings and conclusions in the paper are unbiased .Despite these limitations, our study provides sound estimates of unit costs of HCT and PMTCT services in Nigeria. Considering the sample size, sampling strategy, and aspects of service provision analyzed, this is the most comprehensive study on the efficiency of HCT and PMTCT services in Nigeria to date. Our study adds to the literature on the efficiency of HIV programs and illuminates determinants of cost variation. Our results could be used to inform program design to optimize the use of resources and sustain coverage of HIV services.S1 File(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableDependent variable is the natural logarithm of unit cost.(XLSX)Click here for additional data file.S6 TableDependent variable is the natural logarithm of unit cost.(XLSX)Click here for additional data file.