N = 21,813) from 6,962 households were surveyed and tested for malaria. An infection was defined as testing positive for Plasmodium falciparum by either a conventional or novel highly sensitive rapid diagnostic test. Seropositivity to the early transcribed membrane protein 5 antigen 1 represented recent exposure to P. falciparum. Clusters were identified using SaTScan. Associations among individual, household, and environmental risk factors for malaria, recent exposure, and living in spatial clusters of these outcomes were evaluated. Malaria infection was detected in 161 individuals (median age: 15 years). Weighted malaria prevalence was low . Serological evidence of recent exposure was detected in 1,134 individuals. Bed net use, household wealth, and elevation were protective, whereas being febrile, over age 5 years, and living in either households with rudimentary wall material or farther from the road increased the odds of malaria. Two predominant overlapping spatial clusters of infection and recent exposure were identified. Individual, household, and environmental risk factors are associated with the odds of individual risk and recent exposure in Artibonite; spatial clusters are primarily associated with household-level risk factors. Findings from serology testing can further strengthen the targeting of interventions.Targeting malaria interventions in elimination settings where transmission is heterogeneous is essential to ensure the efficient use of resources. Identifying the most important risk factors among persons experiencing a range of exposure can facilitate such targeting. A cross-sectional household survey was conducted in Artibonite, Haiti, to identify and characterize spatial clustering of malaria infections. Household members ( The stu2 contiguous operational units (OUs); 476 OUs had inhabited, residential households ranging from 1 to 1,627 households. Households were the primary sampling unit and were selected by simple random sampling within each OU to ensure spatial distribution across the study area. To maximize the precision of estimates, sample sizes for each OU were dependent on the population size of the OU, which were categorized into three strata: 1) large OUs (> 200 households); 2) medium OUs (20–200 households); and 3) small OUs (< 20 households). Ten percent of households in large OUs were sampled, 20 households (10–100%) were sampled in medium OUs, and 100% of households in small OUs were sampled. An additional 5% of households in large and medium OUs were oversampled to accommodate expected household-level refusals.A complete georeferenced census of the study area was conducted from June 1 to 22, 2017, prior to the household survey. The study area was subdivided into 1 × 1-kmSampled households were visited from July 17 to October 4, 2017 . Maps of the study area with houses, roads, and key landmarks were created and uploaded onto tablets to assist in navigation to the sampled households using the PDF Maps application . The survey instrument and sample tracking were programmed into CommCare (Dimagi). Data collected during the census, including household coordinates, head of household name, and household description, were uploaded into CommCare to assist the teams in locating the selected households. An interviewer and a laboratory technician visited the sampled households and obtained consent, administered the questionnaire, tested for malaria using rapid diagnostic tests (RDTs), and collected blood samples for serology testing.The survey consisted of two sets of questions, one for the head of household (HoH) and one for the primary caretaker (CT), if different. The HoH and/or CT were asked questions about malaria knowledge; information, education, and communication; care-seeking behavior; mobility; acceptability of an MDA; and socioeconomic status. Additionally, the demographics of each household member, along with bed net use (last night), recent travel (outside the home subcommune within 3 months), and previous residence (within 24 months) were collected. All consenting household members had their axillary temperature measured and a finger prick blood sample for malaria diagnosis taken by a conventional RDT  and a highly sensitive RDT .Schistosoma japonicum glutathione S-transferase (GST) were measured using a multiplex bead assay with GST as a nonbinding control because Etramp 5 ag 1 is expressed with a GST purification tag. Assay protocol and quality control processes were previously described.,At the LNSP, antibody responses  to early transcribed membrane protein 5 antigen 1 (Etramp 5 ag 1) and Up to three visits per household were attempted before the household was recorded as unavailable. Similarly, up to two return visits for absent household members who were expected to return within 2 days of the initial survey were attempted following the same procedures described above.For survey participation and malaria diagnostic testing, informed consent from HoHs and/or CTs for and their children < 18 years of age, consent from all individual adult members, and assent from children aged 7–17 years were obtained and documented electronically. The study was approved by the Haitian Ministry of Public Health and Population Bioethics Committee, the Institutional Review Board of the CDC, and the London School of Hygiene & Tropical Medicine Ethics Committee.P. falciparum by either cRDT or HS-RDT. Although the national policy in Haiti only allowed the use of cRDTs for the diagnosis and treatment of malaria, a nested study comparing the performance of cRDT versus HS-RDT provided results from the novel HS-RDTs, which have been shown to detect slightly more infections.P. falciparum .,,10-transformed MFI participant data, and the threshold for seropositivity was defined as the mean of the lower distribution plus 5 SDs.P. falciparum were identified using purely retrospective spatial models with Poisson distributions in SaTScan . Unweighted estimates of parasite prevalence by OU were calculated and mapped. The overall weighted parasite prevalence was estimated using the survey estimation commands in Stata SE version 15.1  to account for the complex survey design .A malaria infection was defined as an individual testing positive for The univariate and adjusted associations between infections and concordant negatives (those who tested negative by cRDT and HS-RDT) among potential individual, household, and environmental risk factors for individual malaria risk, and for risk of living in a spatial infection cluster, were evaluated using the survey estimation commands in Stata SE version 15.1. For adjusted models, sex and age category were selected a priori. These methods were repeated for the serologic marker of recent exposure analyses.In addition to demographic and individual characteristics, several covariates were tested in the models. Euclidian distances from the household to each of the nearest health facility, river, and road were derived using ArcGIS Desktop version 10.5.1 . Population density by OU was determined using census data. A household wealth index categorized into quintiles was derived using principal-components analysis of several fields that took into account ownership of durable assets  and access to utilities and infrastructure  as per the approach used during the Demographic Health Survey.Weather and environmental variable data used in this analysis were extracted from the Climate Hazard Group Infrared Precipitation (CHIRPS) and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. CHIRPS data have been made available by the US Geological Survey and involve satellite data merged with archived station data.P < 0.05 was considered statistically significant.The method of purposeful selection of covariates was used to determine the final adjusted models.Supplemental Table 1, with travel being the most common reason documented (55.1%). Fifteen percent of selected households were reported as abandoned or locked since the time of the census.Of the 33,060 inhabited households identified during the 2017 complete census in the study area, 8,818 were sampled  to participate in the household survey. Among these sampled households, 7,338  had an HoH and/or CT available to approach to consent to participate; 1,465 (16.6%) were unavailable. Survey data were lost for 15 (0.2%) households because of application or tablet malfunctions. The reasons for a household’s unavailability are categorized in Supplemental Figure 1 depicts a flow diagram from the number of sampled households to the numbers of completed surveys. In summary, completed surveys were recorded from 6,962 households in total, consisting of 5,952 HoH surveys and 2,537 CT surveys. The average household size was 3.8 members (SD = 2.1).During the initial visit, 6,020 (68.3%) households were closed, meaning they were available to provide consent or refuse to participate in the survey. A second visit was required to close 961 (10.9%) households, and 1,822 (20.7%) households required three visits to close.Supplemental Figure 2). More males  than females  were absent (P < 0.001). Nearly one-third  of absent individuals were traveling overnight outside his/her home subcommune, and 36.1% of these individuals were traveling outside of Artibonite Department. Several individuals refused a blood draw because they were recently tested for malaria . A comprehensive list of reasons for refusal is categorized in Supplemental Table 2.Among the 6,962 households with completed surveys, 26,351 household members (present and absent) were rostered and 21,813 (82.8%) were present and consented to a blood draw (The median age of household members was 19 years (interquartile range [IQR]: 8–40) and 53.9% were female. Only 95 (0.4%) were febrile by axillary temperature, and 5.9% reported sleeping under a bed net the night before the survey. The vast majority (88.3%) reported living in the same house location during the past 24 months, and recent travel within the past 3 months was low (3.7%). Characteristics of consenting individuals are presented in Supplemental Figure 2 illustrates the flow diagram of rostered individuals and samples collected for testing. Data from 21,771 individuals with household GPS coordinates and survey data are included in the risk factor for malaria analysis. Among these, 21,102 (96.8% of samples) were individuals ≥ 1 year old who had acceptable negative responses to the GST internal assay control and linked to households with survey data for use in the analysis of the risk factor for marker of recent exposure to P. falciparum.A total of 21,830 household members had RDT results captured, and 21,801 had a blood sample spotted onto FP for serology testing. 161 P. falciparum infections identified . The median age of infected individuals was 15 years . Weighted malaria prevalence in the study area was low , yet four significant, including two predominant, spatial infection clusters were identified in Verrettes (N = 106) were within identified spatial infection clusters. Recent exposure, defined as Etramp 5 ag 1 seropositivity, was detected in 1,134 individuals (5.2%). Three significant spatial clusters of marker of recent exposure to P. falciparum were identified: two in similar locations as the predominant spatial infection clusters in Verrettes, plus one in La Chapelle  and wealth  were maintained (P = 0.01), whereas elevation was protective . Individuals living in a household with rudimentary wall material had an increased odds of malaria as compared with those living in a household with finished wall material  . Living in a household farther from the nearest road increased the odds of malaria . Significant climate variables included in the final model were prior month mean rainfall  and enhanced vegetation index during the same month as the RDT . In addition, as compared with individuals aged < 5 years, individuals aged 5 to < 15 years and individuals aged 15+ had increased odds of malaria .In the final adjusted model, the protective effect of bed net use . A less pronounced but still significant protective effect of elevation on recent exposure was also seen . Living farther from the nearest road increased the odds of recent exposure . Finally, as compared with individuals aged < 5 years, individuals aged 15+ had increased odds of malaria   were similarly included. Evidence for a protective effect of wealth was weaker in the recent exposure analysis, although as compared with those living in households among the poorest quintile there was a significant protective effect among individuals living in households in the median quintile  .P < 0.01), had rudimentary wall material , had rudimentary floor material , and were farther from the road   .P < 0.001)  were also seen. Additionally, lower population density decreased the likelihood of living in a spatial cluster of recent exposure  .P. falciparum, suggesting recent and ongoing transmission in these areas, which corroborates results from another study conducted in this area.P. falciparum was also detected in La Chapelle. The latter indicates an area with higher recent, but not current, malaria transmission. This is plausible because the incidence of malaria in La Chapelle in 2016 prior to the survey was higher than that of Verrettes  .This large household survey was the first of its kind to characterize and systematically map malaria transmission foci in Haiti. Two predominant spatial case clusters  in Verrettes were identified in similar locations for both infection status and marker of recent exposure to P. falciparum.––The protective risk factors for malaria such as household wealth and individual bed net use identified in this study have been shown in other studies. As household wealth increases, risk for malaria tends to decrease, and this trend has been seen in Haiti and elsewhere, for both risk of malaria and risk of recent exposure to An. albimanus, and more likely driven by cases located in the Terre Natte subcommune (western mountainous region of the study area), where 71 (44.1%) cases were found. At the time of the survey in 2017, there was no functioning health facility within 5 km of the subcommune boundaries. The health facility located in Terre Natte had not been functioning for several years prior to, during, and after the survey . Additionally, in Terre Natte, the monthly mean rainfall (prior month) among households was less (154 mm) than the remainder of the study area (202 mm).Interestingly, the crude elevations are higher among cases than controls; however, elevation is protective in the adjusted models, as has been shown in other studies. And although an increase in rainfall is generally considered a risk factor for malaria, the opposite was found in this study. This is unlikely due to the breeding, biting, or resting habits of An. albimanus, the primary vector for P. falciparum in Haiti. Although the movement and introduction of malaria cases in the Terre Natte subcommune from lower-lying communities cannot be ruled out, autochthonous transmission with An. albimanus or other vectors must also be considered. Studies and a model have suggested that the range of An. albimanus may be increasing to higher elevations.,Anopheles pseudopunctipennis, which have been described in Haiti and also been found at higher elevations, are also present at these highland or mountainous communities.,–Transmission of malaria in this high elevation of Haiti goes against the accepted niche of Although numbers were low, not surprisingly, an individual who was febrile had an increased odds of current malaria infection as detected by RDT. Also, not surprisingly, this association was not found in the serology analyses, which modeled associations with recent exposure to malaria where any associated fever would have likely resolved.,Rudimentary wall material was also found to have significantly increased the odds of malaria than finished wall material. This has been found elsewhere, including in Haiti, and is likely due to rudimentary wall materials enabling mosquito entry more easily than finished wall materials.Sex and age categories were included in the models a priori. Sex did not have a significant effect in any models; however, increasing age categories had increased odds of both malaria and recent exposure. This is not uncommon because malaria occurs among individuals of all ages in areas of low transmission because immunities are not built or sustained with limited exposure.The household survey had several limitations. First, the duration was longer than expected and spanned the rainy and dry seasons (July 17 to October 4), with a pause in data collection from September 6 to 24 due to hurricane threats. Only one case and seven recent exposures were detected after the pause; however, 98% of the samples were already collected by this time. By design, to promote geographic variation in daily sample collection, up to 35 teams on any given day were deployed to different regions across the study area throughout the duration of the survey.Limitations in the data include the potential for misclassification of recent travel among non-HoH or non-CT household members because recent travel was not asked directly of all household members by design for survey efficiency reasons. Instead, the HoH and CT were asked whether he or she traveled during the past 3 months, and if so, whether he or she had travel companions. If yes, the household member(s) who traveled during the (up to) five most recent trips was identified and the other household members were assumed to have not traveled. Therefore, any recent travel by a household member other than the HoH or CT, without the HoH or CT, was not captured. Additionally, because of the survey design, the HoH occupation and education levels of the HoH and CT were only suitable for univariate analyses so as not to drastically trim the sample size of the multivariable analyses. In each univariate analysis, individuals living in a household with an HoH who worked in an agricultural/farmer occupation had statistically significantly higher odds of the respective model outcome than those living in households with an HoH in other occupations.This study demonstrated that individual, household, and environmental risk factors are associated with the odds of individual risk of malaria and recent exposure in La Chapelle and Verrettes, Artibonite Department, but that spatial clusters are primarily associated with risk factors at the household level. These findings can be incorporated into future algorithms or screening tools intended to identify high-transmission foci without the need for intensive household surveys. Additionally, this household survey identified two predominant spatial clusters of malaria that overlapped with clusters of recent exposure that led to further investigation and action by the Ministry of Health.Supplemental materials


FAS), rs4197 (FADD), rs3834129 and rs59308963 (CASP8), rs61079693 (CASP9), rs4647655 (CASP3), rs11269260 (BCL-2), and rs17880560 (TP53)—and the influence of genetic ancestry with susceptibility to malaria and parasite density in an admixed population from the Brazilian Amazon.In malaria infection, apoptosis acts as an important immunomodulatory mechanism that leads to the elimination of parasitized cells, thus reducing the parasite density and controlling immune cell populations. Here, it was investigated the association of INDEL variants in apoptotic genes—rs10562972  DEL/DEL genotype vs. INS/DEL + INS/INS; and (ii) INS/INS vs. INS/DEL + DEL/DEL.Plasmodium falciparum had significantly higher African ancestry proportions in comparison to uninfected controls, Plasmodium vivax, and mixed infections. The INS/INS genotype of rs3834129 (CASP8) seemed to increase the risk for P. falciparum infection , while the DEL/DEL genotype presented a significant protective effect against infection by P. falciparum  and mixed infection , and was associated with lower parasite density in P. falciparum malaria . Additionally, the INS/INS genotype of rs10562972 (FAS) was more frequent among individuals infected with P. vivax compared to P. falciparum , and the DEL/DEL genotype of rs17880560 (TP53) was significantly more present in patients with mono-infection by P. vivax than in individuals with mixed infection .Individuals infected by In conclusion, variants in apoptosis genes are associated with malaria susceptibility and parasite density, indicating the role of apoptosis-related genetic profiles in immune responses against malaria infection.The online version contains supplementary material available at 10.1186/s12936-023-04729-6. Plasmodium, which are transmitted to humans by Anopheles mosquitoes [Plasmodium falciparum, Plasmodium vivax and Plasmodium malariae by mono or mixed infection caused by multiple species of Plasmodium [Malaria is an infection caused by parasites of the genus squitoes . Accordisquitoes . In Brazsquitoes –4, with asmodium .In human malaria, cellular immune response involves the secretion of high levels of pro-inflammatory cytokines, such as tumour necrosis factor (TNF) , interfeFAS, FADD, and CASP8 in the extrinsic/death receptor pathway; (ii) BCL-2 and CASP9 in the intrinsic/mitochondrial pathway; (iii) TP53 and CASP3 in both pathways or the executing phase [These immune components can activate apoptosis, a form of regulated cell death (RCD) associated with the immune response against malaria –19. Apopng phase .Plasmodium antigens, which are phagocytized by dendritic cells (DCs) that, in turn, present the antigens to CD8+ T cells. Failures in this process may contribute to parasite survival, replication in the host, and higher parasite density [+ T cells [+ T cells [Apoptosis is widely considered a non-lytic form of cell death, although it has a dynamic role in the immunity to malaria . For ins density . On the  density , CD8+ T  T cells , and CD4 T cells  depletioPlasmodium infection and the rates of parasite density. This study aimed to investigate the association between the genotypic distribution of eight INDEL markers of apoptosis with the susceptibility to P. falciparum, P. vivax, and mixed infection, and the rates of malaria parasite density in a population of the Brazilian Amazon that presents high levels of genetic admixture.Therefore, the regulated expression of the aforementioned genes is crucial for the proper functioning of apoptosis in the immune response. INDEL variants that alter the activity of encoded apoptotic proteins  may affePlasmodium test, individuals with a positive result were included in the case group of the study. In the blood collection, a questionnaire was applied to assess demographic and epidemiological data, wherewith all participants were asked about their age, sex and history of malaria exposure.Our cohort consisted of 126 patients from Belém (51) and Tucuruí (75), who were diagnosed with malaria after examination of their thick blood smear (TBS), from 2006 to 2010. The samples were collected when participants sought the health service to perform the The control group (CG) was composed of 101 individuals of the general population from Belém with no history of malaria, collected at the Human and Medical Genetics Laboratory in the Federal University of Pará. Both infected individuals and the CG resided in malaria endemic areas and were randomly selected.P. falciparum; (ii) 26 mono-infected with P. vivax; and (iii) 58 individuals with mixed species of Plasmodium infection .As previously reported by our group , the malPeripheral blood samples were collected in tubes containing ethylenediaminetetraacetic acid (EDTA) as an anticoagulant. DNA extraction was based on the phenol–chloroform protocol , and DNAP. falciparum, P. vivax, and P. malariae mitochondrial DNA (mtDNA) following an established method [All infected samples were first diagnosed as positive by TBS, as recommended by the Brazilian Ministry of Health, before proceeding with real-time quantitative PCR (RT-qPCR). Next, malaria parasites were detected by RT-qPCR, based on the amplification of d method . Parasitd method .2), slope, and intercept were evaluated. Standard curve and threshold of detection are shown in Additional file The quantification of parasite density was obtained by the standard curve method. To construct the standard curve, a serial dilution of the genomic DNA in ultra-pure water DF 10) was performed until the concentration of 1:100,000 in triplicate. The serial dilutions were performed in the AriaMx Real-time PCR System  in a final volume of 10 µL containing 3.7 µL of water, 5.0 µL of TaqMan Universal PCR Master Mix, 0.3 µL of TaqMan probe and 1.0 µL of DNA. Next, parameters of the qPCR standard curves such as efficiency, coefficient of determination (r0 was perT) and the construction of the standard curve for P. malariae were not performed given that all the malaria cases caused by P. malariae observed in this study occurred as mixed infections, therefore parasite density of this species could not be reliably estimated by TBS and qPCR.It should be noted that the detection of the threshold cycle , 5.0 μL of QIAGEN Multiplex PCR Master Mix , 1.0 μL of Q-solution, 1.0 μL of primer mix and 2.0 μL of water, as previously established .Amplification was conducted on the ABI Veriti thermal cycler (Thermo Fisher Scientific) using the following program: 95 °C for 15 min, followed by 35 cycles of 94 °C for 45 s, 60 °C for 90 s, and 72 °C for 1 min, with a final extension at 70 °C for 30 min. For fragment analysis, 1.0 μL of PCR product was added to 8.5 μL of HI-DI deionized formamide (Thermo Fisher Scientific) and 0.5 μL of GeneScan 500 LIZ pattern size standard (Thermo Fisher Scientific).v.3.2 software (Thermo Fisher Scientific). The multiplex PCR reaction and fragment analysis of the AIMs were similar to the protocol described above for the apoptosis panel.DNA fragments were separated using ABI PRISM 3130 genetic analyzer (Thermo Fisher Scientific) and analyzed with GeneMapper ID v. 4.0.5  adopting P ≤ 0.05 as statistically significant. Firstly, we calculated the Hardy–Weinberg Equilibrium (HWE) of each variant in the investigated groups using the chi-squared test corrected by the Bonferroni method. Ancestry indices were compared between groups using Mann–Whitney’s U test. While for the comparison of age, sex, and malaria infection history was used Student’s t-test, Pearson’s chi-squared and Fisher’s exact tests, respectively.Statistical analyses were conducted in R software The association between the apoptosis INDEL variants, susceptibility to malaria, and parasite density were evaluated using a multivariate logistic regression to estimate Odds Ratio (OR) at 95% confidence intervals (CI). In the association analyses, genomic ancestry, age, sex, and infection history to control were considered as potential confounding effects.P. vivax vs control group, P = 0.020; P. falciparum vs control group, P = 0.003; mixed infection vs control group, P = 0.013)   Table . The disP. falciparum, P. vivax, mixed infection patients, and control group are represented in Additional file vs INS/DEL + INS/INS; and (ii) carriers of INS/INS genotype vs INS/DEL + DEL/DEL.The allelic frequencies of variants analyzed in P. vivax, significant associations with the risk for infection were not observed  may increase the susceptibility to P. falciparum infection in approximately twofold , while the DEL/DEL genotype of this marker indicated a significant genetic protection effect for P. falciparum infection   (Table For ed Table . The anaFAS) was significantly more frequent among those infected with P. vivax than those with P. falciparum   was also higher among those with mono-infection of P. vivax compared to those with mixed infection   due to their skewed distribution. Moreover, the P-value and OR were adjusted for covariates that showed a significant effect on parasite density according to other studies, such as genetic ancestry, age, sex, and infection history [P, and OR values are presented in Additional file The effect of variants on parasite density was also investigated. For this analysis, the measurements of parasite density were log-transformed  was associated with lower rates of parasite density  , and the infection by P. falciparum, P. vivax, and mixed infection, focusing on susceptibility to infection and parasite density. It was also investigated the potential influence of genomic ancestry in the susceptibility to malaria parasitosis considering the high admixture of the Brazilian Amazon population and that genomic ancestry has been associated with susceptibility to infectious diseases [Therefore, in this study, it was investigated the association between eight INDEL variants in apoptosis-related genes , rs3834129 (CASP8), and rs17880560 (TP53) and at least one of the malaria parameters, suggesting that these INDELs may influence the risk of malaria onset in the occurrence of Plasmodium infection as well as on parasite levels.Importantly, after correcting for African ancestry and other possible confounding factors in the association analysis between the investigated variants and susceptibility to malaria and parasite density, results showed significant associations between rs10562972 , in which the DEL/DEL genotype was more frequent in non-infected individuals, and the INS allele was had higher frequencies in the HPV-positive group, while also associated with the risk of developing more severe clinical forms of HPV, especially in women of African ancestry [These observations differ from the results obtained by Pinto and colleagues , in whicancestry , 46.CASP8 in T cells [CASP8 expression was associated with apoptosis of infected cells, as well as with the death of T cells and other immune cells in the spleen [To date, the effects of the rs3834129 variant on apoptosis, specifically under an infectious condition, are still unknown. However, it has been demonstrated that this variant influences the surveillance of immune cells by suppressing the site where the Specific Protein 1 (SP1) transcription factor binds to the promoter, causing decreased expression of  T cells . Indeed,e spleen .CASP8 promoter may provide genetic protection to their carriers against infection and high parasite density by promoting the survival of T cells, increasing the efficiency of the immune response.It is widely known that T cells play a crucial role in controlling parasite density by killing infected cells, and it occurs through the production of pro-inflammatory cytokines such as TNF and IFN-γ, in addition to the release of granzymes, perforins, and free radicals , 49. ApoPlasmodium species showed differences in the genotypic distribution of rs10562972 (FAS) and rs17880560 (TP53) variants. The INS/INS genotype of rs10562972 (FAS) was identified as a risk factor for malaria caused by P. vivax when compared to P. falciparum.The other INDELs that showed a positive association in the present study are lesser known, and there is a lack of studies associating them with different types of diseases or other phenotypes. However, these variants seem to have a potential effect on protein expression, which can be reinforced by our work and should be further explored. Comparing infection by different FAS gene plays an important role in both the apoptosis of pathogen-infected cells [P. vivax in individuals from the Brazilian Amazon has been found [P. falciparum-associated severe malaria in Ghanaian children [The ed cells  and in Ted cells . Howeveren found , as wellchildren .TP53) as protective against mixed infection in the analysis P. vivax vs mixed infection. Currently, there are no studies reporting the effect of this variant on malaria. However, a functional study showed that TP53−/− mice presented considerably higher parasite density compared to mice with overexpressed TP53 [TP53, decreasing the apoptosis of infected cells.Another interesting finding was the observation of the DEL/DEL genotype of rs17880560 (sed TP53 . This coFAS) and rs17880560 (TP53) are involved in the species-specific immune response to malaria, although it is not possible to establish its role in susceptibility yet, considering the biochemical effects of these mutations have not been assessed. Due to the great heterogeneity in the allelic distribution among populations [Interestingly, the results suggest that the intronic variants rs10562972  is a potential biomarker for susceptibility to P. falciparum and mixed infections, and it might influence parasite density. This study also highlights differences in the genotypic distribution of rs10562972 (FAS) in P. vivax vs P. falciparum and of rs17880560 (TP53) in the comparison between P. vivax and mixed infection, evidencing that genetic profile plays a role in species-specific susceptibility. Importantly, this is most likely the first study with this kind of approach for malaria infection in the Brazilian Amazon.In conclusion, identifying new molecular mechanisms involved in an ancient disease, such as malaria, can aid in the development of new drugs that will mitigate the impact of malaria on public health, considering the high rates of morbidity and mortality , especially in regions in South America and Africa. In this context, rs3834129  Threshold cycle detection for 10-fold dilutions of P. vivax. (B) Standard curve by DNA serial dilution containing 104 to 10-1P. vivax parasites per µL amplified in triplicate. The parameters of the standard curve are given by efficiency, coefficient of determination (r2), slope, and intercept values.Additional file 2: Fig. S2. Graphs of parasite density quantification estimated by RT-qPCR using the serial dilution of DNA from P. falciparum-infected patients. (A) Threshold cycle detection for 10-fold dilutions of P. vivax. (B) Standard curve by DNA serial dilution containing 104 to 10-1P. falciparum parasites per µL amplified in triplicate. The parameters of standard curve are given by efficiency, coefficient of determination (r2), slope and intercept values.Additional file 3: Table S1. Allele frequencies of INDELs for the eight investigated polymorphisms.Additional file 4: Table S2. Comparison of genotypic distribution of P. falciparum- and P. vivax-malaria.Additional file 5: Table S3. Comparison of genotypic distribution of and P. vivax-malaria and mixed infection.Additional file 6: Table S4. Comparison of genotypic distribution of and P. falciparum-malaria and mixed infection.Additional file 7: Table S5. Parasite density levels in P. vivax according to the genotypes.Additional file 8: Table S6. Parasite density levels in P. falciparum according to the genotypes.


P. falciparum endemicity such as the Democratic Republic of Congo (DRC), where 12% of the world’s malaria cases and 13% of deaths occur.Increasing reports suggest that non-falciparum species are an underappreciated cause of malaria in sub-Saharan Africa, but their epidemiology is not well-defined. This is particularly true in regions of high P. malariae and P. ovale spp. infection detected by real-time PCR were estimated among children and adults within a longitudinal study conducted in seven rural, peri-urban, and urban sites from 2015-2017 in Kinshasa Province, DRC. Participants were sampled at biannual household survey visits (asymptomatic) and during routine health facility visits (symptomatic). Participant-level characteristics associated with non-falciparum infections were estimated for single- and mixed-species infections. Among 9,089 samples collected from 1,565 participants over a 3-year period, the incidence of P. malariae and P. ovale spp. infection was 11% (95% CI: 9%-12%) and 7% (95% CI: 5%-8%) by one year, respectively, compared to a 67% (95% CI: 64%-70%) one-year cumulative incidence of P. falciparum infection. Incidence continued to rise in the second year of follow-up, reaching 26% and 15% in school-age children (5-14yo) for P. malariae and P. ovale spp., respectively. Prevalence of P. malariae, P. ovale spp., and P. falciparum infections during household visits were 3% (95% CI: 3%-4%), 1% (95% CI: 1%-2%), and 35% (95% CI: 33%-36%), respectively. Non-falciparum malaria was more prevalent in rural and peri-urban vs. urban sites, in school-age children, and among those with P. falciparum co-infection. A crude association was detected between P. malariae and any anemia in the symptomatic clinic population, although this association did not hold when stratified by anemia severity. No crude associations were detected between non-falciparum infection and fever prevalence.The cumulative incidence and prevalence of P. falciparum remains the primary driver of malaria morbidity and mortality in the DRC. However, non-falciparum species also pose an infection risk across sites of varying urbanicity and malaria endemicity within Kinshasa, DRC, particularly among children under 15 years of age. As P. falciparum interventions gain traction in high-burden settings like the DRC, continued surveillance and improved understanding of non-falciparum infections are warranted. Plasmodium malariae and Plasmodium ovale spp. have increased across sub-Saharan Africa, where more than 95% of global malaria cases and deaths occur.1Plasmodium falciparum is the primary cause of malaria morbidity and mortality in the region. However, molecular surveys have confirmed co-circulating non-falciparum species, and suggest a rise in prevalence in regions where P. falciparum has declined.6 Despite this, our understanding of infection risk and clinical burden posed by non-falciparum species is limited, particularly within regions of high P. falciparum transmission .Reports of non-falciparum malaria caused by 7 indicating a critical need to understand the full landscape of malaria transmission and infection in the country. The DRC harbors the second highest burden of malaria worldwide, accounting for 12% of global malaria cases and 13% of malaria-related deaths as of 20201. Transmission is largely stable and perennial throughout the country, with an estimated 97% of the population living in high malaria transmission regions for eight or more months per year10. While the majority of the country is characterized as hyper- and holo-endemic for malaria12, transmission can vary within and across provinces due to environmental and geographical factors such as urbanicity, population density, land use, temperature, and rainfall13. In Kinshasa Province, home to the capital city of Kinshasa, malaria transmission is lower within the central urban areas, and increases among the outer peri-urban and rural zones10.The Democratic Republic of Congo (DRC) is one of 11 malaria “High Burden, High Impact” countries designated by the World Health Organization (WHO),P. falciparum accounts for the vast majority of infections in the DRC, P. malariae and P. ovale spp. have been documented at low-level prevalences in the DRC16; however, their epidemiology and clinical impact remains poorly understood. Existing non-falciparum prevalence estimates were largely derived from cross-sectional studies, limiting risk assessment, or focused on a singular age group or symptomatic status, which restricts broader generalizability22. The absence of reliable field diagnostics for these less-common infections complicates surveillance efforts and case management. Gold-standard microscopy methods can detect non-falciparum parasites, but insufficient training and specialization ultimately limits the sensitivity and specificity for non-falciparum infections.23 Widely-used malaria rapid diagnostic tests (RDTs) in Africa cannot distinguish P. malariae or P. ovale spp. infections. While most RDTs detect P. falciparum-specific histidine-rich protein 2 (HRP2), and some also detect Plasmodium lactate dehydrogenase (LDH), no P. malariae and P. ovale spp.-specific RDTs are currently available. Further, clinical diagnosis of a non-falciparum infection is not feasible in the absence of symptoms attributed specifically to P. malariae or P. ovale spp. These infections are complicated to detect in malaria-endemic regions such as the DRC where P. falciparum co-infection is common, making it difficult to distinguish symptoms caused by these non-falciparum species. P. malariae infections have been associated with acute febrile illness and anemia26 as well as chronic nephrotic syndrome28. Clinical relevance of P. falciparum co-infection with non-falciparum species is also unclear, with posited suppressive effects observed in one study4, while another detected severe malaria among mixed-infections25. These diagnostic challenges are exacerbated by low parasite densities characteristic of non-falciparum infections, which require the use of sensitive laboratory assays that are not suitable for routine field use.While Plasmodium malariae and P. ovale spp. infections have occasionally been dismissed as rare infections that are not clinically impactful in high-burden countries like the DRC. However, improved characterization of their epidemiology and clinical implications is needed to determine their proper place in malaria programmatic and surveillance efforts. Leveraging a 34-month longitudinal cohort study conducted across diverse sites in Kinshasa Province, DRC, we sought to determine the epidemiology of P. malariae and P. ovale spp. infections in the context of high P. falciparum transmission. We perform high-throughput, real-time PCR on samples collected from both asymptomatic and symptomatic participants of all ages as part of a large longitudinal study of non-falciparum malaria infection. We estimate incidence, risk factors, and clinical features associated with P. malariae and P. ovale spp. infections over time, and as compared to P. falciparum infections.30 In brief, households were selected at random within villages, and household members were enrolled into the study following screening for eligibility criteria and provision of informed consent, or assent for minors. Participants were followed prospectively through biannual household visits , and at visits to local study health facilities, as-needed, for presentation of fever or other malaria symptoms   . HousehoP. falciparum-specific HRP2 and pan-plasmodium lactate dehydrogenase (LDH) antigens . Those positive by RDT (defined as a positive result for either antigen) were referred to study clinics for antimalarial treatment. Where consented, dried blood spot (DBS) samples were also collected at each visit using Whatman 3MM filter paper , and were stored with desiccant at −20°C for future molecular testing.At baseline and follow-up surveys, household-level and individual-level questionnaires were collected to ascertain demographic information, household characteristics , health status and clinical data . Participants were screened for malaria infection at each visit using a combination RDT detecting Brief clinical questionnaires were collected from participants at each symptomatic clinic visit throughout the study, alongside malaria RDTs, DBS samples, and hemoglobin testing. Participants were treated at health facilities according to local clinical judgment, as needed, including artemisinin-based combination therapy (ACT) for malaria infection, or referral for blood transfusion if severely anemic.Plasmodium species. DNA was extracted from DBS samples using Chelex and saponin32. P. falciparum parasitemia was identified using a quantitative real-time duplex polymerase chain reaction (PCR) assay targeting the lactate dehydrogenase (pfldh) and human beta-tubulin genes, as previously described.33 We tested samples for P. malariae and P. ovale spp. parasitemia using a semi-quantitative, duplex real-time PCR assay targeting the 18S ribosomal subunit  <40. P. falciparum samples were run in duplicate and were considered positive if at least one sample amplified at a Ct <38, or both amplified between Cts ≥38 and <40, as previously described.35 Semi-quantitative P. malariae and P. ovale spp. parasite densities were estimated from standard curves made using serially-diluted 18S rRNA plasmid DNA (BEI Resources: #MRA-179 and #MRA-180), assuming six plasmid copies per parasite genome.36 Non-falciparum parasitemias were then multiplied by 4.0 to account for a 4-fold dilution of blood from three DBS punches37, improving comparability with P. falciparum parasitemia quantification. DNA samples with evidence of dehydration were rehydrated prior to PCR testing using 50μL of molecular-grade water; rehydrated samples were excluded from parasite density analyses. Negative (water) controls were included on all PCR runs.Samples underwent molecular testing at the University of North Carolina Chapel Hill to distinguish  subunit .34 A sinAll participants with a baseline DBS available for testing were included in the study. The Kinshasa longitudinal cohort study population provided two distinct types of data utilized in this study: 1) The “survey-based” analysis consists of participant survey data and clinical samples collected at active surveillance household visits for all those enrolled, and 2) the “clinic-based” analysis consists of participant survey data and clinical samples collected from the subset of the surveyed population who visited study clinics as-needed when symptomatic (passive surveillance).Samples derived from all study touchpoints (household surveys + clinic visits) were combined to estimate overall infection burden, and also stratified by population type (survey vs. clinic) to account for differences between their predominantly asymptomatic vs. symptomatic nature. Characteristics between the broader survey population and the nested clinic subpopulation were assessed , and weiP. malariae, P. ovale spp., and P. falciparum infection confirmed by real-time PCR. Demographic and clinical characteristics were summarized by Plasmodium species across study populations, and the incidence and prevalence of infections were estimated across the 34-month study follow-up period. Parasite densities were descriptively summarized by species and infection type (mixed vs. single-species).The primary outcomes in this study were P. malariae, P. ovale spp., and P. falciparum infections were calculated using Kaplan-Meier methods among participants who were PCR-negative at baseline for the Plasmodium species of interest. Incidences were estimated as the inverse of the survival function, measuring time (months) to the first detected infection since baseline. Participants in the survey population were censored at the time of their last study household visit. Participants in the clinic sub-population were censored at the end of passive surveillance follow-up, as participants were eligible to continue visiting study health clinics even after the final active follow-up, if symptomatic. Participants dropped out of the at-risk population at the time of their first infection event. We assumed no competing risks for malaria infection, a plausible assumption since malaria infection by one species would not preclude infection by another, and mortality events able to be measured in the study were low . Demographic characteristics associated with incidence of infection were evaluated by log-rank testing of stratified cumulative incidence curves.Cumulative incidences of P. malariae, P. ovale spp., and P. falciparum were estimated overall, and by infection type, calculated as the number of infections detected out of the total number of visits in the study. Factors associated with non-falciparum infection prevalences were evaluated using binomial generalized estimating equations (GEEs) to account for repeated testing of participants over time. An exchangeable working correlation matrix was assumed for GEE models, and robust standard errors were estimated for calculation of 95% confidence intervals (CIs). We also assessed the frequency of multiple same-species non-falciparum infections detected within a participant throughout follow-up; however, these were not distinguished between acute re-infection events, or chronic carriage of a prior infection.Prevalences of 38; quintiles were collapsed into three categories for analysis, and wealth at baseline was carried forward for all subsequent study visits. Seasonality was defined by month, classifying October through April as the rainy season. Anemia severity at symptomatic clinic visits was classified according to hemoglobin (Hb) level, following World Health Organization (WHO) categories for age-, sex-, and pregnancy-specific cut-points;40 severe anemia was defined as Hb<7.0 g/dL for children <5 years, and Hb<8.0 g/dL for all others. Cases were categorized as any anemia, and comparing moderate to severe with mild or no anemia cases. Fever was defined as an axillary temperature >37.5°C measured at symptomatic clinic visits, or as self-reported fever within the prior week at baseline and follow-up surveys. Missing data were summarized and excluded from statistical analyses.Household wealth was computed through adaptation of the Demographic and Health Survey (DHS) method and categorized into quintiles as previously describedtidycmprsk, ggsurvfit, and gee packages. Informed consent, and assent where required, was obtained from all participants or their legal guardians prior to study enrollment and sampling. The study was approved by the Institutional Review Boards at the University of North Carolina at Chapel Hill (IRB#: 14-0489) the University of Iowa (#201701201), and the Kinshasa School of Public Health (ESP/CE/015/014).Dataset construction and cleaning were performed using SAS (version 9.4), and analyses were conducted in R (version 4.0.2) using A total of 1,591 individuals were enrolled in the parent cohort across 242 households and seven sites in Kinshasa Province, DRC. Among these, 1,565 (98.4%) participants had a baseline DBS sample available for analysis and were included in this study, contributing 5,682 total visits. Participant follow-up by analysis population is displayed in P. falciparum infection, 3% a P. malariae infection, and 0.4% a P. ovale spp. infection.Baseline demographic and clinical characteristics for the survey population are summarized in P. malariae and P. ovale spp. infection at baseline, respectively; 69.1%  were PCR-negative for a P. falciparum infection. These PCR-negative participants comprised at-risk populations for malaria incidence estimation.Baseline characteristics were similar between those also included in the symptomatic clinic subpopulation, and the full survey population . The medP. malariae and P. ovale spp. infections were 10.6% (95% CI: 8.7%-12.4%) and 6.7% (95% CI: 5.2%-8.2%), respectively, encompassing incident infections detected at survey or clinic visits. Comparatively, 67.2% (95% CI: 63.9%-70.2%) of all participants acquired a P. falciparum infection by 1-year  and 3.5% (95% CI: 2.5%-4.4%), respectively, including single- and mixed-species infections, whereas the cumulative incidence of any P. falciparum infection by 1-year was 43.1% (95% CI: 39.9%-46.1%) within the survey population . Time to the first detected P. ovale spp. infection was similar between children <5 and 5-14 years throughout follow-up, whereas school-aged children 5-14 years old experienced a faster time to P. malariae infection, particularly towards the end of follow-up driven by symptomatic clinic-based infections. The cumulative incidence of P. falciparum infection was also higher among children <5 and 5-14 years old, compared to adults aged ≥15, although P. falciparum incidences were high (>60%) across all age categories by 1-year (p=0.003). No differences in the cumulative incidence of P. ovale spp. and P. falciparum infection by sex were detected , although P. malariae infection incidence was higher among males than females (p=0.02). Incidence of P. malariae, P. ovale spp., and P. falciparum infections over time was similar between rural and peri-urban settings, but was significantly lower among urban households (p<0.001 across species), with risk of P. malariae and P. ovale spp. close to zero in urban areas across the full study period encompassing survey and clinic-based infections.Cumulative incidences of non-falciparum and P. malariae infection, and 1.4% (95% CI: 1.1%-1.7%) for P. ovale spp. infection. Prevalence of P. falciparum infection was higher at 34.9% (95% CI: 33.2%-36.5%). The majority of P. malariae and P. ovale spp. infections in the survey-based population were mixed-species , and were predominately co-infected with P. falciparum. In contrast, the vast majority of P. falciparum infections were single-species .Crude prevalence of non-falciparum infection was lower in household survey visits than symptomatic clinic visits, as expected. Across all household surveys, we observed a crude period prevalence of 3.3% (95% CI: 2.8%-3.8%) for P. malariae (4.0% [95% CI: 3.3%-4.7%]) and P. ovale spp.  compared to the survey population.Similar prevalences to those detected in the survey population were observed among the symptomatic clinic subpopulation, for P. malariae prevalence across household survey visits remained steady throughout follow-up, fluctuating between 3.0% at baseline, 2.4% at follow-up 1, 4.1% at follow-up 2, and 3.7% at the final household survey. Similarly, P. ovale spp. prevalence remained relatively low throughout follow-up, with 0.4% of the population infected with P. ovale spp. at baseline, increasing to 1.9% and 2.0% at follow-ups 1 and 2, and ending at a 1.4% prevalence by the final follow-up. The timeline of non-falciparum infections by participant throughout the study are depicted in P. malariae infection, and in 21.6% (n=30/139) of those with a P. ovale spp. infection during the 34-month study period. Three participants each had a P. malariae infection detected 4 times throughout follow-up. In comparison, P. falciparum infections re-occurred frequently, with 75.2% (n=914/1216) of those who had a P. falciparum infection having more than one during follow-up, and 22.4% (n=272/1216) having ≥5 P. falciparum infections detected.P. malariae infection in the survey-based population was highest among school-aged children aged 5-14 years at 5.6% (95% CI: 4.4-6.7%), though still low overall, followed by children <5 years (3.4% [95% CI: 2.1-4.7%]), and lowest among those aged ≥15 (1.7% [95% CI: 1.2%-2.2%]). Conversely, children <5 years experienced a slightly higher prevalence of P. ovale spp. infection compared to school-aged children (2.3% [95% CI: 1.3%-3.3%] vs. 1.9% [95% CI: 1.2%-2.7%]), although prevalences across both age groups were low overall, and lower than P. malariae prevalence in these age groups; 0.7% (95% CI: 0.4% - 1.0%) of adults ≥15 years had a P. ovale spp. infection at study survey visits.Children had non-falciparum infections more frequently than adults. Prevalence of P. falciparum prevalence differences in P. falciparum coinfection was associated with an increased prevalence of both P. malariae and P. ovale spp. infections. In comparison to those with average wealth, higher wealth was associated with a decreased prevalence of P. malariae and P. ovale spp. infection. School-aged children 5-14 years old were associated with a higher prevalence of P. malariae and P. ovale spp. infection as compared to participants 15 and older, and also as compared to children aged <5 for P. malariae. Similarly, in the clinic-based analysis, school-aged children were also associated with an increased prevalence of P. malariae and P. ovale spp., infections, compared to adults ≥15 and older; however, prevalence was similar between children <5 years and adults ≥15 and older in this symptomatic population. Likewise, no associations were observed with P. falciparum co-infection for either non-falciparum species.Factors associated with the prevalence of non-falciparum infections are shown in P. malariae (PD: −0.006 [95% CI:−0.018-0.006]) and P. ovale spp. infections (PD: 0.007 [95% CI: −0.002-0.017]), as compared to no malaria infection among the survey population , although associations were no longer significant when stratifying by anemia severity, comparing moderate-to-severe cases vs. mild or no anemia for P. malariae (PD: 0.012 [95% CI: −0.006-0.029]), or for P. ovale spp. , while P. falciparum parasite densities in the total population were higher at 267  p/μL. Non-falciparum parasite densities remained low when stratified by asymptomatic survey population , vs. symptomatic clinic sub-population . Parasite density distributions were slightly higher among P. malariae infections than P. ovale spp. infections. We did not detect any differences in estimated P. malariae or P. ovale spp. parasite density distributions between mixed- vs. single-species P. malariae or P. ovale spp. infections in the total population , or across specific population types. Parasite densities are summarized in Estimated median (IQR) parasite densities were low (<50 p/μL) among all non-falciparum infections in the study  and P. falciparum- P. ovale co-infections  as compared to single-species P. falciparum infections among the asymptomatic survey population. However, a lower median P. falciparum parasite density was observed within mixed P. falciparum- P. malariae infections compared to P. falciparum single-species infections in the clinic-based sub-population ; this association was not observed for P. falciparum- P. ovale co-infections , although the sample size for mixed P. falciparum-P. ovale co-infections was smaller than for single-species P. falciparum infections.Interestingly, differences in the distribution of ale spp. . A higheP. falciparum transmission intensities in Kinshasa Province, DRC. In the largest longitudinal study of non-falciparum malaria conducted to-date in the DRC, we observed an 11% cumulative incidence of P. malariae infection, and 7% incidence of P. ovale spp. infection within one-year, including both asymptomatic and symptomatic infections. Over two-thirds of the study population in this high malaria burdened country had an incident P. falciparum infection within one year, confirming the central importance of P. falciparum in the DRC. Over 70% of the non-falciparum infections detected occurred as co-infections with P. falciparum. Though P. falciparum was the dominant species, we detected a considerable risk of infection by a non-falciparum species, particularly for children under 15 years of age. These findings underscore the need to consider these neglected species in areas of high P. falciparum transmission.Non-falciparum malaria infection was common in this study, affecting children and adults across a range of P. malariae infection during the study, and 7% had at least one P. ovale spp. infection, amounting to 3% and 1% P. malariae and P. ovale spp. infection prevalence at study visits across follow-up, including both mixed- and single-species infections. Similar prevalences were observed among symptomatic individuals. Prevalences generally align with previous estimates of non-falciparum infections in the DRC derived from cross-sectional studies41. Infection prevalences were stable across the 34-month follow-up, differing from recent studies in neighboring countries which have detected increases in P. malariae and P. ovale infection prevalence over time, particularly as P. falciparum prevalences have started to decline6. The high proportion of P. malariae-infected participants who experienced multiple infections in the study (24%) is notable given that this species is known to recrudesce. Chronic P. malariae infection may be associated with deleterious clinical outcomes, such as severe anemia and chronic nephrotic syndrome42. Though we could not distinguish whether multiple P. malariae infections were chronic occurrences or acute re-infection events, future work may allow us to differentiate these infection types. Such work is necessary given the dearth of evidence on the commonality and timing of non-falciparum infection recrudescence, as well as reinfection rates for non-falciparum species in regions highly endemic for P. falciparum.Ten percent of asymptomatic household survey participants had at least one P. malariae and P. ovale spp. infection were similar but not identical to those at risk for P. falciparum. School-aged children were found to have higher prevalences of P. malariae infection than children under 5 years of age, following similar age-related infection associations with P. falciparum that have been previously established in the region43. Dissimilar from P. falciparum infection patterns, symptomatic children under 5 had comparable P. malariae infection prevalences as those experienced by symptomatic adults aged 15 and older. All Plasmodium species were generally more common in rural and peri-urban sites, and less common in the wealthiest households.Populations at risk for P. malariae infection prevalence and anemia of any severity in the symptomatic clinic subpopulation, which translated to a 1.5% absolute increase in prevalence compared to those without anemia. Although this association was no longer significant when stratifying by anemia severity, and was not detected among P. ovale spp. infections in this study. Similarly, no association with non-falciparum infections and fever was detected within the survey- or clinic-based analyses, though misclassification of fever is possible in the setting of fever-reducing medicines taken prior to clinic visits, for example. Whether fever-reducing medicines were taken was not captured in the study. Prior studies have posited a protective association between non-falciparum-P. falciparum co-infections and lower prevalences of clinical malaria outcomes as compared to single-species P. falciparum infections45, although this has not been consistently observed across studies47. We did not assess causal effects of non-falciparum infection on clinical outcomes in our study (though no crude associations were detected), including possible attenuation of symptomatic P. falciparum due to mixed-species infections.We observed a crude association between P. falciparum parasite densities were higher in mixed infections with P. malariae or P. ovale spp. in the household survey-based, but not clinic-based, analysis. One possible explanation is that P. falciparum increases its virulence to compete with non-falciparum species within the asymptomatic host, though our data are insufficient to evaluate this hypothesis. Non-falciparum parasite densities observed in this study were low, as is characteristic of P. malariae and P. ovale spp. infections. We did not identify any difference in non-falciparum parasite density between mixed and single-species non-falciparum infections.Interestingly, Our incidence and prevalence estimates should be considered lower bounds of the true incidence and prevalence in the study catchment area owing to several limitations of the study. First, while loss to follow-up was low overall in the study, missed study visits, early loss to follow-up, and differences in study health clinic attendance across sites may have introduced selection bias into the study. Participants may have elected to visit alternative health facilities for malaria care instead of presenting to study clinics. However, as all participants were eligible for free treatment at study clinics, the clinic sub-population is likely to be representative of the overall study population. Second, our duplex PCR assay detected low density infections but would likely miss those with very low densities. Third, the biannual frequency of household surveys missed infections that occurred and resolved between study visits. Similarly, while the longitudinal design provides helpful insight into risk of infection surrounding these species, even 34-months of follow-up is likely insufficient to detect changes in the prevalence of these less-common species over time in the DRC, where gains in malaria control have not been achieved as in other settings. Fourth, some misclassification of seasonality may be present, as local classifications for seasonality by month, rather than rainfall amounts, were used to define rainy seasons. Finally, our observational study design is not immune from the risk of unmeasured confounding, although no causal relationships were assessed in this study as risk factors depict crude associations, and the large sample size improves confidence in our conclusions.P. falciparum. Though less common and impactful than P. falciparum, P. malariae and P. ovale spp. infections occurred frequently and were often detected within symptomatic cases in this large longitudinal study in the DRC. Malaria research and control efforts focused on P. falciparum should consider these neglected species, particularly in school-aged children and rural communities.This study provides insight into the epidemiology of non-falciparum species in a region heavily affected by Supplement 1Supplement 2


DIC in severe falciparum malaria and fatal malaria was 14.6%  and 82.2% . The estimates of DIC among severe malaria patients who had multi-organ dysfunction with bleeding, cerebral malaria, acute renal failure, and ≥2 complications were 79.6% , 11.9% , 16.7% , and 4.8% , respectively. The proportion estimates of DIC among the patients with malaria depended on the Plasmodium species, clinical severity, and types of severe complications. The information from this study provided useful information to guide the management of malaria patients. Future studies are needed to investigate the association between Plasmodium infection and DIC and to understand the mechanism of malaria-induced DIC.Disseminated intravascular coagulation (DIC) is a potentially life-threatening condition that causes systemic coagulation to be turned on and coagulation factors to be used up. However, the evidence for DIC in malaria patients is still not clear, and small case series and retrospective studies have shown varying results. This meta-analysis was intended for the evaluation of the evidence of DIC among malaria patients using a meta-analysis approach. The protocol for the systematic review was registered at PROSPERO as CRD42023392194. Studies that investigated DIC in patients with malaria were searched in Ovid, Scopus, Embase, PubMed, and MEDLINE. The pooled proportion with 95% confidence intervals (CI) of DIC among malaria patients was estimated using a random-effects model. A total of 1837 articles were identified, and 38 articles were included in the meta-analysis. The overall proportion of DIC in malaria was 11.6% (95% CI: 8.9%–14.3%, I Anopheles mosquitoes infected with Plasmodium species. It is one of the deadliest infectious diseases in humans, which is frequently found in tropical and subtropical areas. Additionally, international travelers and immigrants from endemic countries are a known source of malaria and distribution worldwide ) AND (((Disseminated Intravascular Coagulation) OR (Disseminated Intravascular Coagulation [MeSH Terms])) OR (Consumption Coagulopathy)) OR (Consumption Coagulopathy [MeSH Terms])”. The searches in other databases, including Ovid, Scopus, Embase, and MEDLINE, were slightly modified according to each database (The search strategy was created by using search terms with the Boolean operators “AND” and “OR” as follows: “(“Disseminated Intravascular Coagulation” OR “Disseminated Intravascular” OR “Disseminated Coagulation” OR “Disseminated Coagulations” OR “Consumption Coagulopathy” OR “Consumption Coagulopathies” OR “Intravascular Coagulation” OR “Intravascular Coagulations”) AND . The disagreement over selection between authors was finalized by discussion for consensus.The original studies that investigated the DIC in patients with malaria from inception to 7 January 2023 were included in the present study. Studies without full texts, non-human studies such as animal studies, and in vitro studies were excluded. Non-original articles such as reviews, case reports, letters, notes, and systematic reviews were also excluded. The retrieved studies from the database searches were imported into Endnote version 20.0  for reference management. Before selecting the studies, duplicates were removed by both the automation tool in the Endnote software and manually by the authors. The remaining studies were screened for titles and abstracts and non-relevant studies were excluded. The eligible studies were then examined for full texts against the pre-set criteria. Study selection was performed independently by two authors (TD and MK). The disagreement over selection between authors was resolved by discussion. After the study selection was finalized, the necessary data were extracted into a Microsoft Excel sheet, including information on the name of the first author, publication year, study design, study area, participants (and number), clinical status (complications), age groups, The studies were assessed for their reporting quality based on Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) criteria for observational studies . The STR2-statistic) values of 0–40%, 30–60%, 50–90%, and 75–100% indicated unimportant, moderate, substantial, and considerable heterogeneity, respectively [Plasmodium spp., method for malaria detection, or clinical status, sub-group analyses were performed. The funnel plot and Egger’s test were employed to detect possible publication bias. All analyses were performed using the statistical software Stata Version 17.0 .The pooled proportion with 95% confidence intervals (CI) of DIC among malaria patients was estimated using a random-effects model as described previously by DerSimonian and Laird . Forest ectively . If the A total of 1837 articles were identified from Embase n = 418), MEDLINE n = 247), Ovid n = 576), PubMed (n = 193), and Scopus n = 403). After 793 duplicates had been removed, 1044 articles were screened for their titles and abstracts. Then, 986 non-relevant articles, such as articles that enrolled other diseases rather than malaria were excluded. The remaining 70 articles were further examined for eligibility, and 34 articles were excluded for the following reasons: no full-texts (n = 13), no records of articles (n = 8), unable to extract data (n = 6), non-English articles (n = 3), poster or conference abstracts (n = 2), reviews (n = 1), and an animal study (n = 1). A total of 37 studies [3. After 8, MEDLIN, Ovid  and more than half of them in adult participants (60.5%). More than half of the studies enrolled patients with severe malaria (57.9%), followed by severe and non-severe malaria (34.2%). Microscopy was the most used method for the detection of Plasmodium (65.8%). Details of the studies are shown in A summary of the included studies is shown in According to the STROBE criteria that assessed the study’s quality with an overall score of 22 items, two studies received high scores ,53. The Six studies investigated the evidence of DIC in patients with malaria but no DIC was found ,41,51,562: 93.2%, 38 studies, Plasmodium spp., method for malaria detection, and clinical status showed that the study design, clinical status, and types of complications were the probable sources of heterogeneity of the proportion estimates between the studies , 11.9% , 16.7% , and 4.8% , indicating the existence of a publication bias in the meta-analysis due to a small-study effect or the fact that some studies were missing from the meta-analysis.The funnel plot was asymmetrical  and the Plasmodium parasites, particularly those patients who developed severe malaria.Although the epidemiology of DIC in patients with malaria has been reported in the literature, the real evidence of DIC among malaria patients remains unclear. The present study intended to synthesize the evidence of DIC among malaria patients using data from the literature. The results showed that the pooled estimate of the number of patients with malaria who had DIC was 11.6%. The high proportion of DIC among the patients with malaria indicated a likelihood and a probability of bleeding tendency among the individuals who get infected with Plasmodium infection with an increased risk of mortality and it can be triggered by several pathological mechanisms, including parasite-derived factors, host immune responses, and endothelial damage that can lead to coagulation activation, coagulation inhibitor defect, and impaired fibrinolysis. Endothelial activation is considered a major pathophysiological feature of malarial infection, which is caused by the interaction of parasite-derived molecules with endothelial receptors, resulting in increased expression of adhesion molecules such as von Willebrand factor (vWF) and vWF propeptides [DIC usually occurs in severe peptides . Hollestpeptides . vWF plapeptides . Increaspeptides . In malapeptides . In addipeptides . The activation of the pro-coagulation stage may occur in mild and severe malaria infections caused by various mechanisms. Phosphatidylserine exposure on the infected red blood cell surface membrane triggers the formation of prothrombinase complex . Pro-infEndogenous anticoagulant proteins, including antithrombin, protein C, and protein S are decreased in malarial infection due to high consumption, leakage, and reduced hepatic production. Under normal physiological conditions, protein C is activated by thrombin and forms a complex with thrombomodulin on the endothelial cell surface leading to proteolytic cleavage of factors Va and VIIIa. However, during malarial infection, protein C is inhibited by inflammatory cytokines ,71. TissThe high proportion estimate of DIC among patients with malaria found in the present meta-analysis was due to the variability in the study design, clinical severity, and types of severe complications. In the subgroup meta-analysis of different study designs, the proportion estimate of DIC in malaria was highest in the cohort studies (21%). The high proportion estimate (79.6%) was found in the cohort study by Das et al.  but the P. falciparum infections showed that the highest proportion of DIC among the patients was demonstrated in fatal malaria cases (82.2%). The DIC related-death was reported by several studies and linked to P. falciparum [falciparum malaria, the proportion of DIC was lower than the fatal malaria cases by 14.6%. Moxon et al. showed that the patients with cerebral malaria had a high proportion of DIC (11.9%) [The meta-analysis involving different levels of severity of lciparum ,31,40,44 (11.9%) . Cerebra (11.9%) . The ass (11.9%) ,63,76,77 (11.9%) . The intKidney complication is a common cause of morbidity and mortality in severe malaria infection. The meta-analysis showed that the malarial patients with acute renal failure also had a high proportion of DIC (16.7%). The association between kidney injury and DIC was explained by several studies ,80,81,82Plasmodium species, the meta-analysis showed a higher overall proportion of DIC among the patients with P. falciparum malaria than those with P. vivax malaria (16% versus 3%). These results indicate that P. falciparum infection led to a higher probability of DIC development than P. vivax. The DIC due to P. vivax was scarcely reported in the literature, and mostly as case reports [In the different  reports ,84. Alth reports ,46,53. Plasmodium species. Finally, the information from this study would provide useful information to guide the management of malaria patients.The present study had several limitations. First, the limitation on the quality score of the included studies , may have an impact on the overall proportion estimated in the current study. Second, the heterogeneity of the proportion estimates between the included studies, which remained in the meta-analysis results though the meta-regression and subgroup analyses, indicated that other confounders or some other characteristics of the participants that were unavailable to be retrieved may be the sources of the heterogeneity, but these are still uninvestigated. Third, publication bias due to a small-study effect or because some studies were missing from the meta-analysis was found in the present meta-analysis and may have had an impact on the meta-analysis’s conclusion. More studies are needed to investigate the evidence, probable risk factors, and mechanism of DIC among patients infected with malaria with the different severity levels of malaria or Plasmodium species, and types of severe complications. The information from this study would provide useful information to guide the management of malaria patients. Future studies are needed to investigate the association between Plasmodium infection and DIC and to understand the mechanism of malaria-induced DIC.The present study demonstrated that the pooled proportion estimate of DIC among the patients with malaria was 11.6% and varied between 8.9% and 14.3%. The proportion estimates of DIC among the patients with malaria depended on the clinical severity,