Human Trypanosoma cruzi infection risk is driven by eco-social interactions in rural communities of the Argentine Chaco

The transmission of Trypanosoma cruzi to humans is determined by multiple ecological, socio-economic and cultural factors acting at different scales. Their effects on the human risk of infection with T. cruzi have often been examined separately or using a limited set of ecological and socio-demographic variables. Herein, we integrated the ecological and social dimensions of human disease risk with the spatial distribution patterns of human and vector (Triatoma infestans) infection with T. cruzi in rural communities of the Argentine Chaco composed mainly of indigenous people (90% Qom) and a creole minority. Prior to the implementation of a vector control intervention, the estimated seroprevalence of T. cruzi among 1,929 local residents examined in a cross-sectional study was 29.0%, and was twice as large in Qom than creoles. Using generalized linear mixed models, the risk of human infection increased by 60% with each additional infected triatomine and by 40% with each seropositive household co-inhabitant; increased significantly with increasing household social vulnerability (a multidimensional index of poverty), and decreased with increasing host availability in sleeping quarters. A significant negative interaction between household social vulnerability and the relative abundance of infected T. infestans indicated that vulnerable household residents were exposed to a higher risk of infection even at low infected-vector abundances. Household mobility within the study area reduced the effects of domiciliary vector abundance, possibly due to less consistent exposures. Nonetheless, the seroprevalence rates of movers and non-movers were not significantly different. Human infection was clustered by household and at a larger spatial scale, with hotspots of human and vector infection matching areas of higher social vulnerability. These results were integrated in a risk map that shows high-priority areas for targeted interventions oriented to suppress house (re)infestations, treat infected children, and thus reduce the burden of future disease. Author summary Chagas disease is one of the main neglected tropical diseases (NTDs) affecting vulnerable communities in Latin America where transmission by triatomine vectors still occurs. Access to diagnosis and treatment is one of the remaining challenges for sustainable control of Chagas disease in endemic areas. In this study, we integrated the ecological and social determinants of human infection with the spatial component to identify individuals, households and geographic sectors at higher risk of infection. We found that the risk of human infection was higher in indigenous people compared to creoles, and increased with the abundance of infected vectors and with household social vulnerability (a multidimensional index of poverty). We also found that the social factors modulated the effect of the abundance of infected vectors: vulnerable-household residents were exposed to a higher risk of infection even at low infected-vector abundance, and human mobility within the area determined a lower and more variable exposure to the vector over time. These results were integrated in a risk map that showed high-priority areas, which can be used in designing cost-effective serological screening strategies adapted to resource-constrained areas.


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Author summary 45 Chagas disease is one of the main neglected tropical diseases (NTDs) affecting vulnerable communities in 46 Latin America where transmission by triatomine vectors still occurs. Access to diagnosis and treatment is one of the remaining challenges for sustainable control of Chagas disease in endemic areas. In this study, 48 we integrated the ecological and social determinants of human infection with the spatial component to 49 identify individuals, households and geographic sectors at higher risk of infection. We found that the risk 50 of human infection was higher in indigenous people compared to creoles, and increased with the 51 abundance of infected vectors and with household social vulnerability (a multidimensional index of 52 poverty). We also found that the social factors modulated the effect of the abundance of infected vectors: Introduction 83 cruzi has declined over the last 60 years [13][14][15], it remains high (27.8-71.1%) in rural communities 84 encompassing creole and indigenous populations [16][17][18][19][20][21][22][23][24].

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In the Gran Chaco, human infection with T. cruzi usually occurs within sleeping quarters before 86 reaching 15 years of age and is transmitted by Triatoma infestans [25][26][27]. Most studies of human 87 infection with T. cruzi in endemic areas have focused on the seroprevalence distribution among 88 demographic subgroups and/or on the effects of vector presence, abundance and T. cruzi infection status.

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Although the association between human T. cruzi infection and selected socio-demographic factors has 90 been investigated [24,25,[28][29][30][31], these studies either did not address the combined effects of ecological 91 and social variables due to limited data availability, or only considered a few socio-demographic 92 variables. Human infection was positively associated with the presence or abundance of domestic animals 93 [24,25,28,29,32]. A less clear association was found between T. cruzi human infection and house 94 construction quality (i.e., thatched roofs and cracks in the walls): while in some studies human infection 95 increased in poor-quality housing [25,28,31,32], others did not find such association [29,30].

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The joint analysis of the spatial distribution of human and vector infection can shed light into the 97 processes and factors associated with the vector-borne transmission of T. cruzi. Integrating the spatial 98 component of disease with household-level and individual-based risk factor analysis is needed to identify 99 transmission hotspots, create risk maps of T. cruzi infection, and stratify the affected areas for targeted 100 control [33][34][35]. For Chagas disease, spatial analysis has been used to investigate the reinfestation process 109 levels. We also considered the household socio-economic status and the interaction between social and 110 ecological variables using indices of social vulnerability (as a measure of socio-economic inequalities) We also evaluated the interaction between vector abundance, the social 252 vulnerability and host availability indices, and retained in the model the ones that had a significant effect.

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We compared a GLMM model (logit link function) considering the household as a random variable and a 254 GLM model in both cases.

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We used an information theoretic approach and Akaike's information criterion (AIC) to identify the best-256 fitting models given the data collected, and a multimodel inference approach to account for model in older adults (Fig 2). Although females had a lower overall seroprevalence rate than males (26.5 vs 308 31.6%; χ 2 test, df =1, p = 0.04), this difference was more evident in adults (Fig 2) and was not significant 309 after adjusting for age (S1 Table). The seroprevalence for Qom people almost doubled that observed for 310 creoles (29.7 vs 18.7%; χ 2 test, df = 1, p = 0.02) (S1 Table).  (Fig 3). In both cases, the effects of the socio-364 demographic variables were additive, as the interaction terms were not significant. The occurrence and 365 abundance of T. cruzi-seropositive children were similar to the distribution of infected domiciliary T.

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infestans, which also increased with host availability and social vulnerability (Fig 4).   Table).

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The proportion of houses with at least one seropositive child in 2008 also varied significantly between 391 communities (χ 2 test; df = 2; p < 0.01). The highest proportion was found in Cuarta Legua compared to 392 the other communities (32.9% vs. 14.5-13.8%, respectively), but no spatial aggregation was found    Table).

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Human infection was significantly clustered by household, after adjusting for the abundance of infected 417 vectors, household social vulnerability and host availability (β household = 1.3, CI 95 = 1.02-1.7, log-likelihood 418 ratio test, p < 0.001). When we included the number of seropositive co-inhabitants, the random effect of 419 the household was nil and no significant differences were found between the GLMM and the respective 420 GLM model (log-likelihood ratio test, p = 1), indicating that all variables included in the model accounted 421 for the differences among households.

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The risk of T. cruzi infection increased with age and if they were Qom, but did not vary by gender (Table   423 2

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In both models, VIF<2 indicated no multicollinearity issues. The infection risk model for the total 445 population had AUC = 0.83, with a sensitivity of 83% and a specificity of 72% (Fig 7).  Fig 7), and it had higher sensitivity (87%) and lower specificity (68%) 451 than the previous model. It predicted 28.8% of false positive cases but only 1.1% of false negatives.

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The risk maps derived from the interpolation of the risk model documented the heterogeneous distribution 457 of human infection and the occurrence of high-risk areas, which were more widespread when the total 458 population was considered (Fig 8A) compared to the children risk map (Fig 8B). Although they failed to 459 include a few households with seropositive children, most households with human cases were 460 encompassed in these high-risk areas.  Table). This study shows the multivariate relationship among the ecological, demographic and socio-economic other indigenous (59-71%) and creole (40-62%) communities living in more disadvantaged, isolated areas 490 of Chaco province known as "The Impenetrable" [17,18,21], and in the Bolivian Chaco (40-80%) [31,67]. the 1980s when the intensity of vector-borne transmission was much higher [68], and remains evident 494 almost three decades later.

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The heterogeneous distribution of human infection was also captured within the studied communities 496 through spatial analysis. Human cases, especially among children, were aggregated (Fig 5, S3 Fig)