Dataset Information

Schistosoma haematobium infection and environmental factors in Southwestern Tanzania: A cross-sectional, population-based study.

ABSTRACT: Schistosomiasis is a leading cause of morbidity in Africa. Understanding the disease ecology and environmental factors that influence its distribution is important to guide control efforts. Geographic information systems have increasingly been used in the field of schistosomiasis environmental epidemiology. This study reports prevalences of Schistosoma haematobium infection and uses remotely sensed and questionnaire data from over 17000 participants to identify environmental and socio-demographic factors that are associated with this parasitic infection. Data regarding socio-demographic status and S. haematobium infection were obtained between May 2006 and May 2007 from 17280 participants (53% females, median age = 17 years) in the Mbeya Region, Tanzania. Combined with remotely sensed environmental data (vegetation cover, altitude, rainfall etc.) this data was analyzed to identify environmental and socio-demographic factors associated with S. haematobium infection, using mixed effects logistic regression and geostatistical modelling. The overall prevalence of S. haematobium infection was 5.3% (95% confidence interval (CI): 5.0-5.6%). Multivariable analysis revealed increased odds of infection for school-aged children (5-15 years, odds ratio (OR) = 7.8, CI: 5.9-10.4) and the age groups 15-25 and 25-35 years (15-25 years: OR = 5.8, CI: 4.3-8.0, 25-35 years: OR = 1.6, CI: 1.1-2.4) compared to persons above 35 years of age, for increasing distance to water courses (OR = 1.4, CI: 1.2-1.6 per km) and for proximity to Lake Nyasa (<1 km, OR = 4.5, CI: 1.8-11.4; 1-2 km, OR = 3.5, CI: 1.7-7.5; 2-4 km; OR = 3.3, CI: 1.7-6.6), when compared to distances >4 km. Odds of infection decreased with higher altitude (OR = 0.7, CI: 0.6-0.8 per 100 m increase) and with increasing enhanced vegetation index EVI (OR = 0.2, CI: 0.1-0.4 per 0.1 units). When additionally adjusting for spatial correlation population density became a significant predictor of schistosomiasis infection (OR = 1.3, CI: 1.1-1.5 per 1000 persons/km2) and altitude turned non-significant. We found highly focal geographical patterns of S. haematobium infection in Mbeya Region in Southwestern Tanzania. Despite low overall prevalence our spatially heterogeneous results show that some of the study sites suffer from a considerable burden of S. haematobium infection, which is related to various socio-demographic and environmental factors. Our results could help to design more effective control strategies in the future, especially targeting school-aged children living in low altitude sites and/or crowded areas as the persons at highest need for preventive chemotherapy.

SUBMITTER: Manz KM

PROVIDER: S-EPMC7446842 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Schistosoma haematobium infection and environmental factors in Southwestern Tanzania: A cross-sectional, population-based study.

Manz Kirsi M KM Kroidl Inge I Clowes Petra P Gerhardt Martina M Nyembe Wilbrod W Maganga Lucas L Assisya Weston W Ntinginya Nyanda E NE Berger Ursula U Hoelscher Michael M Saathoff Elmar E

PLoS neglected tropical diseases 20200824 8

Schistosomiasis is a leading cause of morbidity in Africa. Understanding the disease ecology and environmental factors that influence its distribution is important to guide control efforts. Geographic information systems have increasingly been used in the field of schistosomiasis environmental epidemiology. This study reports prevalences of Schistosoma haematobium infection and uses remotely sensed and questionnaire data from over 17000 participants to identify environmental and socio-demographi ...[more]

PMID: 32833959

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Project description:BackgroundHookworm disease is one of the most common infections and cause of a high disease burden in the tropics and subtropics. Remotely sensed ecological data and model-based geostatistics have been used recently to identify areas in need for hookworm control.MethodologyCross-sectional interview data and stool samples from 6,375 participants from nine different sites in Mbeya region, south-western Tanzania, were collected as part of a cohort study. Hookworm infection was assessed by microscopy of duplicate Kato-Katz thick smears from one stool sample from each participant. A geographic information system was used to obtain remotely sensed environmental data such as land surface temperature (LST), vegetation cover, rainfall, and elevation, and combine them with hookworm infection data and with socio-demographic and behavioral data. Uni- and multivariable logistic regression was performed on sites separately and on the pooled dataset.Principal findingsUnivariable analyses yielded significant associations for all ecological variables. Five ecological variables stayed significant in the final multivariable model: population density (odds ratio (OR)?=?0.68; 95% confidence interval (CI)?=?0.63-0.73), mean annual vegetation density (OR?=?0.11; 95% CI?=?0.06-0.18), mean annual LST during the day (OR?=?0.81; 95% CI?=?0.75-0.88), mean annual LST during the night (OR?=?1.54; 95% CI?=?1.44-1.64), and latrine coverage in household surroundings (OR?=?1.02; 95% CI?=?1.01-1.04). Interaction terms revealed substantial differences in associations of hookworm infection with population density, mean annual enhanced vegetation index, and latrine coverage between the two sites with the highest prevalence of infection.Conclusion/significanceThis study supports previous findings that remotely sensed data such as vegetation indices, LST, and elevation are strongly associated with hookworm prevalence. However, the results indicate that the influence of environmental conditions can differ substantially within a relatively small geographic area. The use of large-scale associations as a predictive tool on smaller scales is therefore problematic and should be handled with care.

Project description:BackgroundThe intestinal nematode Trichuris trichiura is among the most common causes of human infectious disease worldwide. As for other soil-transmitted nematodes, its reproductive success and thus prevalence and intensity of infection in a given area strongly depend on environmental conditions. Characterization of the influence of environmental factors can therefore aid to identify infection hot spots for targeted mass treatment.MethodologyWe analyzed data from a cross-sectional survey including 6234 participants from nine distinct study sites in Mbeya region, Tanzania. A geographic information system was used to combine remotely sensed and individual data, which were analyzed using uni- and multivariable Poisson regression. Household clustering was accounted for and when necessary, fractional polynomials were used to capture non-linear relationships between T. trichiura infection prevalence and environmental variables.Principal findingsT. trichiura infection was restricted to the Kyela site, close to Lake Nyasa with only very few cases in the other eight sites. The prevalence of T. trichiura infection in Kyela was 26.6% (95% confidence interval (CI) 23.9 to 29.6%). Multivariable models revealed a positive association of infection with denser vegetation (prevalence ratio (PR) per 0.1 EVI units = 2.12, CI 1.28 to 3.50) and inverse associations with rainfall (PR per 100 mm = 0.54, CI 0.44 to 0.67) and elevation (PR per meter = 0.89, CI 0.86 to 0.93) while adjusting for age and previous worm treatment. Slope of the terrain was modelled non-linearly and also showed a positive association with T. trichiura infection (p-value p<0.001).Conclusion/significanceHigher prevalences of T. trichiura infection were only found in Kyela, a study site characterized by denser vegetation, high rainfall, low elevation and flat terrain. But even within this site, we found significant influences of vegetation density, rainfall, elevation and slope on T. trichiura infection. The inverse association of rainfall with infection in Kyela is likely due to the fact, that rainfall in this site is beyond the optimum conditions for egg development. Our findings demonstrate that use of remotely sensed environmental data can aid to predict high-risk areas for targeted helminth control.

Project description:BackgroundWith one quarter of the world population infected, the intestinal nematode Ascaris lumbricoides is one of the most common infectious agents, especially in the tropics and sub-tropics. Infection is caused by oral intake of eggs and can cause respiratory and gastrointestinal problems. To identify high risk areas for intervention, it is necessary to understand the effects of climatic, environmental and socio-demographic conditions on A. lumbricoides infection.MethodologyCross-sectional survey data of 6,366 study participants in the Mbeya region of South-Western Tanzania were used to analyze associations between remotely sensed environmental data and A. lumbricoides infection. Non-linear associations were accounted for by using fractional polynomial regression, and socio-demographic and sanitary data were included as potential confounders.Principal findingsThe overall prevalence of A. lumbricoides infection was 6.8%. Our final multivariable model revealed a significant non-linear association between rainfall and A. lumbricoides infection with peak prevalences at 1740 mm of mean annual rainfall. Mean annual land surface temperature during the day was linearly modeled and negatively associated with A. lumbricoides infection (odds ratio (OR) = 0.87, 95% confidence interval (CI) = 0.78-0.97). Furthermore, age, which also showed a significant non-linear association (infection maximum at 7.7 years), socio-economic status (OR = 0.82, CI = 0.68-0.97), and latrine coverage around the house (OR = 0.80, CI = 0.67-0.96) remained in the final model.ConclusionsA. lumbricoides infection was associated with environmental, socio-demographic and sanitary factors both in uni- and multivariable analysis. Non-linear analysis with fractional polynomials can improve model fit, resulting in a better understanding of the relationship between environmental conditions and helminth infection, and more precise predictions of high prevalence areas. However, socio-demographic determinants and sanitary conditions should also be considered, especially when planning public health interventions on a smaller scale, such as the community level.

Project description:Urine microscopy is the standard diagnostic method for urogenital S. haematobium infection. However, this may lead to under-diagnosis of urogenital schistosomiasis, as the disease may present itself with genital symptoms in the absence of ova in the urine. Currently there is no single reliable and affordable diagnostic method to diagnose the full spectrum of urogenital S. haematobium infection. In this study we explore the classic indicators in the diagnosis of urogenital S. haematobium infection, with focus on young women.In a cross-sectional study of 1237 sexually active young women in rural South Africa, we assessed four diagnostic indicators of urogenital S. haematobium infection: microscopy of urine, polymerase chain reaction (PCR) of cervicovaginal lavage (CVL), urogenital symptoms, and sandy patches detected clinically in combination with computerised image analysis of photocolposcopic images. We estimated the accuracy of these diagnostic indicators through the following analyses: 1) cross tabulation (assumed empirical gold standard) of the tests against the combined findings of sandy patches and/or computerized image analysis and 2) a latent class model of the four indicators without assuming any gold standard.The empirical approach showed that urine microscopy had a sensitivity of 34.7% and specificity of 75.2% while the latent class analysis approach (LCA) suggested a sensitivity of 81.0% and specificity of 85.6%. The empirical approach and LCA showed that Schistosoma PCR in CVL had low sensitivity (14.1% and 52.4%, respectively) and high specificity (93.0% and 98.0, respectively). Using LCA, the presence of sandy patches showed a sensitivity of 81.6 and specificity of 42.4%. The empirical approach and LCA showed that urogenital symptoms had a high sensitivity (89.4% and 100.0%, respectively), whereas specificity was low (10.6% and 12.3%, respectively).All the diagnostic indicators used in the study had limited accuracy. Using urine microscopy or Schistosoma PCR in CVL would only confirm a fraction of the sandy patches found by colposcopic examination.

Dataset Information

Schistosoma haematobium infection and environmental factors in Southwestern Tanzania: A cross-sectional, population-based study.

Publications

Schistosoma haematobium infection and environmental factors in Southwestern Tanzania: A cross-sectional, population-based study.

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