Uncovering the Spread of an Infectious Disease with Mobile Phone Data

We use mobile phone records for the analysis of mobility patterns and the detection of possible risk zones of Chagas disease in two Latin American countries. We show that geolocalized call records are rich in social and individual information, which can be used to infer whether an individual has lived in an endemic area. We present two case studies, in Argentina and in Mexico, using data provided by mobile phone companies from each country. The risk maps that we generate can be used by health campaign managers to target specific areas and allocate resources more effectively. Finally, we show the value of mobile phone records to predict long-term migrations, which play a crucial role in the spread of Chagas disease.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Uncovering the Spread of an Infectious Disease with Mobile Phone Data

We use mobile phone records for the analysis of mobility patterns and the detection of possible risk zones of Chagas disease in two Latin American countries. We show that geolocalized call records are rich in social and individual information, which can be used to infer whether an individual has lived in an endemic area. We present two case studies, in Argentina and in Mexico, using data provided by mobile phone companies from each country. The risk maps that we generate can be used by health campaign managers to target specific areas and allocate resources more effectively. Finally, we show the value of mobile phone records to predict long-term migrations, which play a crucial role in the spread of Chagas disease.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Uncovering the Spread of an Infectious Disease with Mobile Phone Data

We use mobile phone records for the analysis of mobility patterns and the detection of possible risk zones of Chagas disease in two Latin American countries. We show that geolocalized call records are rich in social and individual information, which can be used to infer whether an individual has lived in an endemic area. We present two case studies, in Argentina and in Mexico, using data provided by mobile phone companies from each country. The risk maps that we generate can be used by health campaign managers to target specific areas and allocate resources more effectively. Finally, we show the value of mobile phone records to predict long-term migrations, which play a crucial role in the spread of Chagas disease.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Retracing Micro-Epidemics of Chagas Disease Using Epicenter Regression

Vector-borne transmission of Chagas disease has become an urban problem in the city of Arequipa, Peru, yet the debilitating symptoms that can occur in the chronic stage of the disease are rarely seen in hospitals in the city. The lack of obvious clinical disease in Arequipa has led to speculation that the local strain of the etiologic agent, Trypanosoma cruzi, has low chronic pathogenicity. The long asymptomatic period of Chagas disease leads us to an alternative hypothesis for the absence of clinical cases in Arequipa: transmission in the city may be so recent that most infected individuals have yet to progress to late stage disease. Here we describe a new method, epicenter regression, that allows us to infer the spatial and temporal history of disease transmission from a snapshot of a population's infection status. We show that in a community of Arequipa, transmission of T. cruzi by the insect vector Triatoma infestans occurred as a series of focal micro-epidemics, the oldest of which began only around 20 years ago. These micro-epidemics infected nearly 5% of the community before transmission of the parasite was disrupted through insecticide application in 2004. Most extant human infections in our study community arose over a brief period of time immediately prior to vector control. According to our findings, the symptoms of chronic Chagas disease are expected to be absent, even if the strain is pathogenic in the chronic phase of disease, given the long asymptomatic period of the disease and short history of intense transmission. Traducción al español disponible en Alternative Language Text S1/A Spanish translation of this article is available in Alternative Language Text S

Retracing Micro-Epidemics of Chagas Disease Using Epicenter Regression

Vector-borne transmission of Chagas disease has become an urban problem in the city of Arequipa, Peru, yet the debilitating symptoms that can occur in the chronic stage of the disease are rarely seen in hospitals in the city. The lack of obvious clinical disease in Arequipa has led to speculation that the local strain of the etiologic agent, Trypanosoma cruzi, has low chronic pathogenicity. The long asymptomatic period of Chagas disease leads us to an alternative hypothesis for the absence of clinical cases in Arequipa: transmission in the city may be so recent that most infected individuals have yet to progress to late stage disease. Here we describe a new method, epicenter regression, that allows us to infer the spatial and temporal history of disease transmission from a snapshot of a population\u27s infection status. We show that in a community of Arequipa, transmission of T. cruzi by the insect vector Triatoma infestans occurred as a series of focal micro-epidemics, the oldest of which began only around 20 years ago. These micro-epidemics infected nearly 5% of the community before transmission of the parasite was disrupted through insecticide application in 2004. Most extant human infections in our study community arose over a brief period of time immediately prior to vector control. According to our findings, the symptoms of chronic Chagas disease are expected to be absent, even if the strain is pathogenic in the chronic phase of disease, given the long asymptomatic period of the disease and short history of intense transmission

The history of Chagas disease

The ancestor of Trypanosome cruzi was probably introduced to South American via bats approximately 7-10 million years ago. When the first humans arrived in the New World, a sylvatic cycle of Chagas disease was then already well established. Paleoparasitological data suggests that human American trypanosomiasis originated in the Andean area when people founded the first settlements in the coastal region of the Atacama Desert. Identification of T. cruzi as the etiological agent and triatome bugs as the transmission vector of Chagas disease occurred within a few years at the beginning of the 20 century. History also teaches us that human activity leading to environmental changes, in particular deforestation, is the main cause for the spread of Chagas disease. Recently, migration of T. cruzi-infected patients has led to a distribution of Chagas disease from Latin America to non-endemic countries in Europe, North America and western Pacific region

Uncovering vector, parasite, blood meal and microbiome patterns from mixed-DNA specimens of the Chagas disease vector Triatoma dimidiata

Chagas disease, considered a neglected disease by the World Health Organization, is caused by the protozoan parasite Trypanosoma cruzi, and transmitted by \u3e140 triatomine species across the Americas. In Central America, the main vector is Triatoma dimidiata, an opportunistic blood meal feeder inhabiting both domestic and sylvatic ecotopes. Given the diversity of interacting biological agents involved in the epidemiology of Chagas disease, having simultaneous information on the dynamics of the parasite, vector, the gut microbiome of the vector, and the blood meal source would facilitate identifying key biotic factors associated with the risk of T. cruzi transmission. In this study, we developed a RADseq-based analysis pipeline to study mixed-species DNA extracted from T. dimidiata abdomens. To evaluate the efficacy of the method across spatial scales, we used a nested spatial sampling design that spanned from individual villages within Guatemala to major biogeographic regions of Central America. Information from each biotic source was distinguished with bioinformatics tools and used to evaluate the prevalence of T. cruzi infection and predominant Discrete Typing Units (DTUs) in the region, the population genetic structure of T. dimidiata, gut microbial diversity, and the blood meal history. An average of 3.25 million reads per specimen were obtained, with approximately 1% assigned to the parasite, 20% to the vector, 11% to bacteria, and 4% to putative blood meals. Using a total of 6,405 T. cruzi SNPs, we detected nine infected vectors harboring two distinct DTUs: TcI and a second unidentified strain, possibly TcIV. Vector specimens were sufficiently variable for population genomic analyses, with a total of 25,710 T. dimidiata SNPs across all samples that were sufficient to detect geographic genetic structure at both local and regional scales. We observed a diverse microbiotic community, with significantly higher bacterial species richness in infected T. dimidiata abdomens than those that were not infected. Unifrac analysis suggests a common assemblage of bacteria associated with infection, which co-occurs with the typical gut microbial community derived from the local environment. We identified vertebrate blood meals from five T. dimidiata abdomens, including chicken, dog, duck and human; however, additional detection methods would be necessary to confidently identify blood meal sources from most specimens. Overall, our study shows this method is effective for simultaneously generating genetic data on vectors and their associated parasites, along with ecological information on feeding patterns and microbial interactions that may be followed up with complementary approaches such as PCR-based parasite detection, 18S eukaryotic and 16S bacterial barcoding

Assessing Community Dynamics and Colonization Patterns of \u3ci\u3eTritatoma dimidiata\u3c/i\u3e and Other Biotic Factors Associated with Chagas Disease Prevalence in Central America

Chagas disease is caused by the parasite Trypanosoma cruzi and transmitted by multiple triatomine vectors across the Americas. In Central America, the predominant vector is Triatoma dimidiata, a highly adaptable and genetically diverse Hemiptera. In this research, we used a novel reduced-representation DNA sequencing approach to discover community dynamics among multiple biotic factors associated with Chagas disease in Central America, and assess the infestation patterns of T. dimidiata after seasonal and chemical disturbances in Jutiapa, Guatemala. For our first study, we used a hierarchical sampling design to obtain multi-species DNA data found in the abdomens of 32 T. dimidiata specimens from Central America. We aimed to understand (1) the prevalence of T. cruzi infection, (2) the population genetics of the vector and parasite, (3) the blood meal history of the vector, and (4) gut microbial diversity. Our results indicated the presence of nine infected vectors harboring two distinct DTUs: TcI and possibly TcIV. We found significant clusters among T. dimidiata populations in countrywide and within-country levels associated with sylvatic ecotopes and diverse domestic genotypes. There was significantly higher bacteria species richness in infected T. dimidiata abdomens than those that were not infected, with further analysis suggesting that gut bacteria diversity relates to both T. cruzi infection and the local environment. We identified vertebrate blood meals from five T. dimidiata abdomens including chicken, dog, duck and human; however, additional detection methods are necessary to confidently identify blood meal sources. In our second study, we analyzed the GBS genotypes of 440 T. dimidiata specimens collected in two towns of Jutiapa, Guatemala. Our aim was to assess (1) the domestic population patterns that aid the recovery of T. dimidiata after an insecticide treatment in El Carrizal and (2) the seasonal changes that regulate the dispersal of the vector in the untreated communities of El Chaperno. Results showed that the insecticide application was effective at reducing the population abundance immediately after the application in El Carrizal; nevertheless, 18-month post-treatment the town-wide infestation and genetic diversity were recovering. Within-house relatedness among specimens recovered 18 months post-treatment, suggesting that the insecticide treatment failed to fully eliminate domiciliated colonies. In contrast, lack of change in abundance or genetic diversity in El Chaperno implied absence of dispersers from sources beyond the town periphery, while evidence of a decrease of relatedness among individuals implied dispersal among houses. After the insecticide treatment in El Carrizal, population reduction led to lack of genetic spatial autocorrelation; nevertheless, rapid dispersal into neighboring houses lead to autocorrelation 18 months after the insecticide treatment. This pattern was also observed in El Chaperno, where an increase in spatial autocorrelation during seasonal dispersal suggests spillover to close-by households. The creation of a novel genomics pipeline allowed us to understand community and dispersal patterns of T. dimidiata and other biotic factors important for the prevalence and transmission of Chagas disease at local and regional levels. Future studies should include complementary approaches for taxa verification (e.g. bacteria 16S barcoding, PCR-base detection), as well as expand the scope of local population analyses to peridomestic and sylvatic genotypes that could suggest a broader range of vector sources and region-wide patterns of temporal and spatial dispersion