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Spatiotemporal variations in exposure: Chagas disease in Colombia as a case study.

ABSTRACT: Age-stratified serosurvey data are often used to understand spatiotemporal trends in disease incidence and exposure through estimating the Force-of-Infection (FoI). Typically, median or mean FoI estimates are used as the response variable in predictive models, often overlooking the uncertainty in estimated FoI values when fitting models and evaluating their predictive ability. To assess how this uncertainty impact predictions, we compared three approaches with three levels of uncertainty integration. We propose a performance indicator to assess how predictions reflect initial uncertainty.In Colombia, 76 serosurveys (1980-2014) conducted at municipality level provided age-stratified Chagas disease prevalence data. The yearly FoI was estimated at the serosurvey level using a time-varying catalytic model. Environmental, demographic and entomological predictors were used to fit and predict the FoI at municipality level from 1980 to 2010 across Colombia.A stratified bootstrap method was used to fit the models without temporal autocorrelation at the serosurvey level. The predictive ability of each model was evaluated to select the best-fit models within urban, rural and (Amerindian) indigenous settings. Model averaging, with the 10 best-fit models identified, was used to generate predictions.Our analysis shows a risk of overconfidence in model predictions when median estimates of FoI alone are used to fit and evaluate models, failing to account for uncertainty in FoI estimates. Our proposed methodology fully propagates uncertainty in the estimated FoI onto the generated predictions, providing realistic assessments of both central tendency and current uncertainty surrounding exposure to Chagas disease.

SUBMITTER: Ledien J

PROVIDER: S-EPMC8759231 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is considered a public health problem in Latin America. In Colombia, it affects more than 437,000 inhabitants, mainly in Casanare, an endemic region with eco-epidemiological characteristics that favor its transmission. The objective of this study was to describe the clinical and epidemiological characteristics of the cases of acute CD in Casanare, eastern Colombia, in the period 2012-2020. Methods: In the present study, 103 medical records of confirmed cases of acute CD were reviewed. The departmental/national incidence and fatality were compared by year; the climatological data of mean temperature, relative humidity, and precipitation per year were reviewed and plotted at IDEAM (Colombian Meteorology Institute) concerning the number of cases of acute CD per month, and it was compared with the frequency of triatomines collected in infested houses by community surveillance. Univariate, bivariate, and multivariate analyses were performed, comparing symptoms and signs according to transmission routes, complications, and age groups. Results: The incidence was 3.16 cases per 100,000 inhabitants, and the fatality rate was 20% in the study period. The most frequent symptoms included: fever 98.1%, myalgia 62.1%, arthralgia 60.2%, and headache 49.5%. There were significant differences in the frequency of myalgia, abdominal pain, and periorbital edema in oral transmission. The main complications were pericardial effusion, myocarditis, and heart failure in the group over 18 years of age. In Casanare, TcI Discrete Typing Unit (DTU) has mainly been identified in humans, triatomines, and reservoirs such as opossums and dogs and TcBat in bats. An increase in the number of acute CD cases was evidenced in March, a period when precipitation increases due to the beginning of the rainy season. Conclusions: The results corroborate the symptomatic heterogeneity of the acute phase of CD, which delays treatment, triggering possible clinical complications. In endemic regions, clinical suspicion, diagnostic capacity, detection, and surveillance programs should be strengthened, including intersectoral public health policies for their prevention and control.

Project description:BackgroundChagas disease is a public health challenge in Colombia, where only an estimated 1.2% of people at risk have accessed diagnosis, while less than 0.5% of affected people have obtained treatment. The development of simplified diagnostic algorithms would enable progress in access to diagnosis; however, the current diagnostic algorithm relies on at least two laboratory-based tests that require qualified personnel, processing equipment, and infrastructure, which are still generally lacking at the primary care level. Rapid diagnostic tests (RDTs) for Chagas disease could simplify diagnosis, but their performance in the epidemiological context of Colombia is not well known.MethodologyA retrospective analytical observational study of RDTs was performed to estimate the operational characteristics of 11 commercially available RDTs designed for in vitro detection of anti-T. cruzi IgG antibodies. The study was performed under controlled laboratory conditions using human serum samples.Principal findingsEleven RDTs were assessed, ten using 585 serum samples and one using 551 serum samples. Employing the current national diagnostic algorithm as a reference standard for serological diagnosis of chronic infection, the sensitivity of the assessed RDTs ranged from 75.5% to 99.0% (95% CI 70.5-100), while specificity ranged from 70.9% to 100% (95% CI 65.3-100). Most tests (7/11, 63.6%) had sensitivity above 90%, and almost all (10/11, 90.9%) had specificity above 90%. Five RDTs had both sensitivity and specificity above 90%.Conclusions/significanceThe evaluation of these 11 commercially available RDTs under controlled laboratory conditions is a first step in the assessment of the diagnostic performance of RDTs in Colombia. As a next step, field studies will be conducted on available RDTs with sensitivity and specificity greater than 90% in this study, to evaluate performance in real world conditions, with the final goal to allow simplified diagnostic algorithms.

Project description:BackgroundFew epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments.MethodsNational spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions.ResultsCalibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 μg/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls.ConclusionsWe demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health.

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Spatiotemporal variations in exposure: Chagas disease in Colombia as a case study.

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