Racial Disparities in Geographic Access to Primary Care in Philadelphia

Although Philadelphia has an adequate supply of primary care providers overall, spatial analysis shows wide variation across neighborhoods, with stark racial disparities. This study identifies six low-access areas within the city that warrant attention

Mapping the Spatial Distribution of a Disease-Transmitting Insect in the Presence of Surveillance Error and Missing Data

Maps of the distribution of epidemiological data often ignore surveillance error or possible correlations between missing information and outcomes. We analyse presence–absence data at the household level (12050 points) of a disease‐carrying insect in Mariano Melgar, Peru, collected as part of the Arequipan Ministry of Health\u27s efforts to control Chagas disease. We construct a Bayesian hierarchical model to locate regions that are vulnerable to under‐reporting due to surveillance error, accounting for variability in participation due to infestation status. The spatial correlation in the data allows us to identify relative inspector sensitivity and to elucidate the relationship between participation and infestation. We show that naive estimates of prevalence would be biased by surveillance error and missingness at random assumptions. We validate our results through simulations and observe how randomized inspector assignments may improve prevalence estimates. Our results suggests that bias due to imperfect observations and missingness at random can be assessed and corrected in prevalence estimates of spatially auto-correlated binary variables

Is Participation Contagious? Evidence From a Household Vector Control Campaign in Urban Peru

Objective: High rates of household participation are critical to the success of door-to-door vector control campaigns. We used the Health Belief Model to assess determinants of participation, including neighbour participation as a cue to action, in a Chagas disease vector control campaign in Peru. Methods: We evaluated clustering of participation among neighbours; estimated participation as a function of household infestation status, neighbourhood type and number of participating neighbours; and described the reported reasons for refusal to participate in a district of 2911 households. Results: We observed significant clustering of participation along city blocks (p\u3c0.0001). Participation was significantly higher for households in new versus established neighbourhoods, for infested households, and for households with more participating neighbours. The effect of neighbour participation was greater in new neighbourhoods. Conclusions: Results support a ‘contagion’ model of participation, highlighting the possibility that one or two participating households can tip a block towards full participation. Future campaigns can leverage these findings by making participation more visible, by addressing stigma associated with spraying, and by employing group incentives to spray

The Effects of City Streets on an Urban Disease Vector.

With increasing urbanization vector-borne diseases are quickly developing in cities, and urban control strategies are needed. If streets are shown to be barriers to disease vectors, city blocks could be used as a convenient and relevant spatial unit of study and control. Unfortunately, existing spatial analysis tools do not allow for assessment of the impact of an urban grid on the presence of disease agents. Here, we first propose a method to test for the significance of the impact of streets on vector infestation based on a decomposition of Moran’s spatial autocorrelation index; and second, develop a Gaussian Field Latent Class model to finely describe the effect of streets while controlling for cofactors and imperfect detection of vectors. We apply these methods to cross-sectional data of infestation by the Chagas disease vector Triatoma infestans in the city of Arequipa, Peru. Our Moran’s decomposition test reveals that the distribution of T. infestans in this urban environment is significantly constrained by streets (p,0.05). With the Gaussian Field Latent Class model we confirm that streets provide a barrier against infestation and further show that greater than 90% of the spatial component of the probability of vector presence is explained by the correlation among houses within city blocks. The city block is thus likely to be an appropriate spatial unit to describe and control T. infestans in an urban context. Characteristics of the urban grid can influence the spatial dynamics of vector borne disease and should be considered when designing public health policies

Characterization of the Dispersal of Non-Domiciliated Triatoma dimidiata through the Selection of Spatially Explicit Models

Chagas disease is one of the most important neglected diseases in Latin America. Although insecticides have been successfully sprayed to control domiciliated vector populations, this strategy has proven to be ineffective in areas where non-domiciliated vectors immigrating from peridomestic or sylvatic ecotopes can (re-)infest houses. The development of strategies for the control of non-domiciliated vectors has thus been identified by the World Health Organization as a major challenge. Such development primarily requires a description of the spatio-temporal dynamics of infestation by these vectors, and a good understanding of their dispersal. We combined for the first time extensive spatio-temporal data sets describing house infestation dynamics by Triatoma dimidiata inside one village, and spatially explicit population dynamics models. The models fitted and predicted remarkably the observed infestation dynamics. They thus provided both key insights into the dispersal of T. dimidiata in this area, and a suitable mathematical background to evaluate the efficacy of various control strategies. Interestingly, the observed and modelled patterns of infestation suggest that interventions could focus on the periphery of the village, where there is the highest risk of transmission. Such spatial optimization may allow for reducing the cost of control, compensating for repeated interventions necessary for non-domiciliated vectors

Optimization of Control Strategies for Non-Domiciliated Triatoma dimidiata, Chagas Disease Vector in the Yucatán Peninsula, Mexico

Chagas disease is the most important vector-borne disease in Latin America. Residual insecticide spraying has been used successfully for the elimination of domestic vectors in many regions. However, some vectors of non-domestic origin are able to invade houses, and they are now a key challenge for further disease control. We developed a mathematical model to predict the temporal variations in abundance of non-domiciliated vectors inside houses, based on triatomine demographic parameters. The reliability of the predictions was demonstrated by comparing these with different sets of insect collection data from the Yucatan peninsula, Mexico. We then simulated vector control strategies based on insecticide spraying, insect, screens and bednets to evaluate their efficacy at reducing triatomine abundance in the houses. An optimum reduction in bug abundance by at least 80% could be obtained by insecticide application only when doses of at least 50 mg/m2 were applied every year within a two-month period matching the house invasion season by bugs. Alternatively, the use of insect screens consistently reduced bug abundance in the houses and offers a sustainable alternative. Such screens may be part of novel interventions for the integrated control of various vector-borne diseases

Jerusalen jittered data

This has the Jerusalen data described in the article, with X/Y jittered to prevent exact recognition of infested households (confidentiality issues). X: longitude in UTM, Y: longitude in UTM, OLDSTATUS: status (infested 0/1) in 2009, STATUS: status (infested 0/1) in 2011

Data from: Two-scale dispersal estimation for biological invasions via synthetic likelihood

Biological invasions reshape environments and affect the ecological and economic welfare of states and communities. Such invasions advance on multiple spatial scales, complicating their control. When modeling stochastic dispersal processes, intractable likelihoods and autocorrelated data complicate parameter estimation. As with other approaches, the recent synthetic likelihood framework for stochastic models uses summary statistics to reduce this complexity; however, it additionally provides usable likelihoods, facilitating the use of existing likelihood-based machinery. Here, we extend this framework to parameterize multi-scale spatio-temporal dispersal models and compare existing and newly developed spatial summary statistics to characterize dispersal patterns. We provide general methods to evaluate potential summary statistics and present a fitting procedure that accurately estimates dispersal parameters on simulated data. Finally, we apply our methods to quantify the short and long range dispersal of Chagas disease vectors in urban Arequipa, Peru, and assess the feasibility of a purely reactive strategy to contain the invasion

Data from: Pyrenean ptarmigan decline under climatic and human influences through the Holocene

In Europe, the Quaternary is characterized by climatic fluctuations known to have led to many cycles of contraction and expansion of species geographical ranges. In addition, during the Holocene, historical changes in human occupation such as colonization or abandonment of traditional land uses can also affect habitats. These climatically or anthropically induced geographic range changes are expected to produce considerable effective populations size change, measurable in terms of genetic diversity and organization. The rock ptarmigan (Lagopus muta) is a small-bodied grouse occurring throughout Northern hemispheric arctic and alpine tundra. This species is not considered threatened at a continental scale, but the populations in the Pyrenees are because of their small population size, geographical isolation, and low genetic diversity. Here, we used eleven microsatellites to investigate genetic variations and differentiations and infer the overall demographic history of Pyrenean rock ptarmigan populations. The low genetic variability found in these populations has been previously thought to be the result of a bottleneck that occurred following the last glacial maximum (i.e., 10,000 years ago) or more recently (i.e., during the last 200 years). Our results clearly indicate a major bottleneck affecting the populations in the last tenth of the Holocene. We discuss how this decline can be explained by a combination of unfavorable and successive events which all increased the degree of habitat fragmentation