Temporal changes in the potential geographic distribution of Histiotus velatus (Chiroptera, Vespertilionidae), the “decade effect”

In Colombia, little is known on the distribution of the Asian mosquito Aedes albopictus, main vector of dengue, chikungunya, and Zika in Asia and Oceania. Therefore, this work sought to estimate its current and future potential geographic distribution under the Representative Concentration Paths (RCP) 2.6 and 8.5 emission scenarios by 2050 and 2070, using ecological niche models. For this, predictions were made in MaxEnt, employing occurrences of A. albopictus from their native area and South America and bioclimatic variables of these places. We found that, from their invasion of Colombia to the most recent years, A. albopictus is present in 47% of the country, in peri-urban (20%), rural (23%), and urban (57%) areas between 0 and 1800 m, with Antioquia and Valle del Cauca being the departments with most of the records. Our ecological niche modelling for the currently suggests that A. albopictus is distributed in 96% of the Colombian continental surface up to 3000 m (p < 0.001) putting at risk at least 48 million of people that could be infected by the arboviruses that this species transmits. Additionally, by 2050 and 2070, under RCP 2.6 scenario, its distribution could cover to nearly 90% of continental extension up to 3100 m (≈55 million of people at risk), while under RCP 8.5 scenario, it could decrease below 60% of continental extension, but expand upward to 3200 m (< 38 million of people at risk). These results suggest that, currently in Colombia, A. albopictus is found throughout the country and climate change could diminish eventually its area of distribution, but increase its altitudinal range. In Colombia, surveillance and vector control programs must focus their attention on this vector to avoid complications in the national public health setting.

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Geographic disparities and socio-demographic predictors of pertussis risk in Florida

PeerJ ◽

10.7717/peerj.11902 ◽

2021 ◽

Vol 9 ◽

pp. e11902

Author(s):

Corinne B. Tandy ◽

Agricola Odoi

Keyword(s):

Resource Allocation ◽

High Risk ◽

Geographic Distribution ◽

Temporal Changes ◽

County Level ◽

Spatial Clusters ◽

Geographic Disparities ◽

Demographic Predictors ◽

Time Period ◽

Over Time

Background Pertussis is a toxin-mediated respiratory illness caused by Bordetella pertussis that can result in severe complications and death, particularly in infants. Between 2008 and 2011, children less than 3 months old accounted for 83% of the pertussis deaths in the United States. Understanding the geographic disparities in the distribution of pertussis risk and identifying high risk geographic areas is necessary for guiding resource allocation and public health control strategies. Therefore, this study investigated geographic disparities and temporal changes in pertussis risk in Florida from 2010 to 2018. It also investigated socioeconomic and demographic predictors of the identified disparities. Methods Pertussis data covering the time period 2010–2018 were obtained from Florida HealthCHARTS web interface. Spatial patterns and temporal changes in geographic distribution of pertussis risk were assessed using county-level choropleth maps for the time periods 2010–2012, 2013–2015, 2016–2018 and 2010–2018. Tango’s flexible spatial scan statistics were used to identify high-risk spatial clusters which were displayed in maps. Ordinary least squares (OLS) regression was used to identify significant predictors of county-level risk. Residuals of the OLS model were assessed for model assumptions including spatial autocorrelation. Results County-level pertussis risk varied from 0 to 116.31 cases per 100,000 people during the study period. A total of 11 significant (p < 0.05) spatial clusters were identified with risk ratios ranging from 1.5 to 5.8. Geographic distribution remained relatively consistent over time with areas of high risk persisting in the western panhandle, northeastern coast, and along the western coast. Although county level pertussis risks generally increased from 2010–2012 to 2013–2015, risk tended to be lower during the 2016–2018 time period. Significant predictors of county-level pertussis risk were rurality, percentage of females, and median income. Counties with high pertussis risk tended to be rural (p = 0.021), those with high median incomes (p = 0.039), and those with high percentages of females (p < 0.001). Conclusion There is evidence that geographic disparities exist and have persisted over time in Florida. This study highlights the application and importance of Geographic Information Systems (GIS) technology and spatial statistical/epidemiological tools in identifying areas of highest disease risk so as to guide resource allocation to reduce health disparities and improve health for all.

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