Exploring the Spatial Determinants of Late HIV Diagnosis in Texas.

INTRODUCTION: Despite statewide progress and continuous HIV prevention efforts in Texas, HIV diagnosis at a late stage of infection persists. Diagnosis delay differs in magnitude and spatial distribution. We examined the local spatial relationships of late HIV diagnosis with a selection of variables in an area of Texas that includes large metropolises and high HIV morbidity. METHODS: We compared regression modeling approaches to study the associations between the regional percentage of late HIV diagnosis from 2011 through 2015, regional measures of poverty, lack of health insurance (uninsurance), educational attainment, unemployment, and the average regional distance from residence to an HIV testing site: global ordinary least squares linear regression, spatial error model, geographically weighted regression, and multiscale geographically weighted regression (MGWR). Cartographic representation of the local R2, coefficient estimates, and their t values assisted in the interpretation of results. RESULTS: The MGWR model resulted in a better fit and identified education and uninsurance as globally fixed predictors, whereas the relationships between late HIV diagnosis and poverty, unemployment, and distance varied spatially. The model performed better in rural areas and in suburban areas of the largest cities than in urban areas. CONCLUSION: The MGWR results provided local estimates of associations. The results highlight the importance of focusing on a local context. Modeling at the local scale is particularly useful for characterizing relationships between explanatory and dependent variables when the relationships vary spatially. In the context of HIV prevention, relationships that are of local relevance can inform local policy and complement routine screening in clinical settings.

Environmental suitability for Aedes aegypti and Aedes albopictus and the spatial distribution of major arboviral infections in Mexico.

BACKGROUND: This paper discusses a comparative geographic distribution of Aedes aegypti and Aedes albopictus mosquitoes in Mexico, using environmental suitability modeling and reported cases of arboviral infections. METHODS: Using presence-only records, we modeled mosquito niches to show how much they influenced the distribution of Ae. aegypti and Ae. albopictus based on mosquito records collected at the municipality level. Mosquito surveillance data were used to create models regarding the predicted suitability of Ae. albopictus and Ae. aegypti mosquitos in Mexico. RESULTS: Ae. albopictus had relatively a better predictive performance (area under the curve, AUC = 0.87) to selected bioclimatic variables compared to Ae. aegypti (AUC = 0.81). Ae. aegypti were more suitable for areas with minimum temperature of coldest month (Bio6, permutation importance 28.7%) -6 °C to 21.5 °C, cumulative winter growing degree days (GDD) between 40 and 500, and precipitation of wettest month (Bio13) >8.4 mm. Minimum temperature range of the coldest month (Bio6) was -6.6 °C to 20.5 °C, and average precipitation of the wettest month (Bio13) 8.9 mm ~ 600 mm were more suitable for the existence of Ae. albopictus. However, arboviral infections maps prepared from the 2012-2016 surveillance data showed cases were reported far beyond predicted municipalities. CONCLUSIONS: This study identified the urgent necessity to start surveillance in 925 additional municipalities that reported arbovirus infections but did not report Aedes mosquito.

Redefining the Australian Anthrax Belt: Modeling the Ecological Niche and Predicting the Geographic Distribution of Bacillus anthracis.

The ecology and distribution of B. anthracis in Australia is not well understood, despite the continued occurrence of anthrax outbreaks in the eastern states of the country. Efforts to estimate the spatial extent of the risk of disease have been limited to a qualitative definition of an anthrax belt extending from southeast Queensland through the centre of New South Wales and into northern Victoria. This definition of the anthrax belt does not consider the role of environmental conditions in the distribution of B. anthracis. Here, we used the genetic algorithm for rule-set prediction model system (GARP), historical anthrax outbreaks and environmental data to model the ecological niche of B. anthracis and predict its potential geographic distribution in Australia. Our models reveal the niche of B. anthracis in Australia is characterized by a narrow range of ecological conditions concentrated in two disjunct corridors. The most dominant corridor, used to redefine a new anthrax belt, parallels the Eastern Highlands and runs from north Victoria to central east Queensland through the centre of New South Wales. This study has redefined the anthrax belt in eastern Australia and provides insights about the ecological factors that limit the distribution of B. anthracis at the continental scale for Australia. The geographic distributions identified can help inform anthrax surveillance strategies by public and veterinary health agencies.

Predictive and epidemiologic modeling of the spatial risk of human onchocerciasis using biophysical factors: a case study of Ghana and Burundi.

Although recent efforts taken have substantially contained human onchocerciasis in many African countries, published reports indicate a recrudescence of the disease. To understand this problem, biophysical factors that favor the establishment of human onchocerciasis in Ghana and Burundi-countries identified as threat locations of recrudescence for neighboring countries-were analyzed. Data pertaining to the prevalence of human onchocerciasis in both countries was obtained from published sources. Findings in this study suggest that there was a gradient in prevalence of onchocerciasis in geographic locations near the water streams. The predictive models suggest that rainfall, humidity, and elevation were statistically significant for Burundi data while in Ghana, only the effect of elevation was highly significant (p<0.0001). In 2010, the estimated at-risk population was 4,817,280 people (19.75% of the total population) and 522,773 people (6.23% of the total population) in Ghana and Burundi, respectively. Findings can help in the effective design of preventive control measures.