During 2012, 2013 and 2015, we collected small mammals within 25 km of the town of Boende in Tshuapa Province, the Democratic Republic of the Congo. The prevalence of monkeypox virus (MPXV) in this area is unknown; however, cases of human infection were previously confirmed near these collection sites. Samples were collected from 353 mammals (rodents, shrews, pangolins, elephant shrews, a potamogale, and a hyrax). Some rodents and shrews were captured from houses where human monkeypox cases have recently been identified, but most were trapped in forests and agricultural areas near villages. Real-time PCR and ELISA were used to assess evidence of MPXV infection and other Orthopoxvirus (OPXV) infections in these small mammals. Seven (2.0%) of these animal samples were found to be anti-orthopoxvirus immunoglobulin G (IgG) antibody positive (six rodents: two Funisciurus spp.; one Graphiurus lorraineus; one Cricetomys emini; one Heliosciurus sp.; one Oenomys hypoxanthus, and one elephant shrew Petrodromus tetradactylus); no individuals were found positive in PCR-based assays. These results suggest that a variety of animals can be infected with OPXVs, and that epidemiology studies and educational campaigns should focus on animals that people are regularly contacting, including larger rodents used as protein sources.

Monkeypox is a zoonotic disease caused by a virus member of the genus Orthopoxvirus and is endemic to Central and Western African countries. Previous work has identified two geographically disjuct clades of monkeypox virus based on the analysis of a few genomes coupled with epidemiological and clinical analyses; however, environmental and geographic causes of this differentiation have not been explored. Here, we expand previous phylogenetic studies by analyzing a larger set of monkeypox virus genomes originating throughout Sub-Saharan Africa to identify possible biogeographic barriers associated with genetic differentiation; and projected ecological niche models onto environmental conditions at three periods in the past to explore the potential role of climate oscillations in the evolution of the two primary clades. Analyses supported the separation of the Congo Basin and West Africa clades; the Congo Basin clade shows much shorter branches, which likely indicate a more recent diversification of isolates within this clade. The area between the Sanaga and Cross Rivers divides the two clades and the Dahomey Gap seems to have also served as a barrier within the West African clade. Contraction of areas with suitable environments for monkeypox virus during the Last Glacial Maximum, suggests that the Congo Basin clade of monkeypox virus experienced a severe bottleneck and has since expanded its geographic range.

Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.

The majority of the Yucatán State, México, presents subtropical climate that is suitable for many species of mosquitoes that are known to be vectors of diseases, including those from the genera Aedes and Culex. The objective of this study is to identify the geographic distribution of five species from these two genera and estimate the human population at risk of coming in contact with them. We compiled distributional data for Aedes aegypti (L.), Aedes (Howardina) cozumelensis (Diaz Najera), Culex coronator Dyar and Knab, Culex quinquefasciatus Say, and Culex thriambus Dyar from several entomological studies in Yucatán between March 2010 and September 2014. Based on these data, we constructed ecological niche models to predict the spatial distribution of each species using the MaxEnt algorithm. Our models identified areas with suitable environments for Ae. aegypti in most of Yucatán. A similar percentage of urban (97.1%) and rural (96.5%) populations were contained in areas of highest suitability for Ae. aegypti, and no spatial pattern was found (Moran’s I = 0.33, P = 0.38); however, we found an association of abundance of immature forms of this species with annual mean temperature (r = 0.19, P ≤ 0.001) and annual precipitation (r = 0.21, P ≤ 0.001). Aedes cozumelensis is also distributed in most areas of the Yucatán State; Cx. quinquefasciatus, Cx. coronator, and Cx. thriambus are restricted to the northwest. The information generated in this study can inform decision-making to address control measures in priority areas with presence of these vectors.

Maps of disease occurrences and GIS-based models of disease transmission risk are increasingly common, and both rely on georeferenced diseases data. Automated methods for georeferencing disease data have been widely studied for developed countries with rich sources of geographic referenced data. However, the transferability of these methods to countries without comparable geographic reference data, particularly when working with historical disease data, has not been as widely studied. Historically, precise geographic information about where individual cases occur has been collected and stored verbally, identifying specific locations using place names. Georeferencing historic data is challenging however, because it is difficult to find appropriate geographic reference data to match the place names to. Here, we assess the degree of care and research invested in converting textual descriptions of disease occurrence locations to numerical grid coordinates (latitude and longitude). Specifically, we develop three datasets from the same, original monkeypox disease occurrence data, with varying levels of care and effort: the first based on an automated web-service, the second improving on the first by reference to additional maps and digital gazetteers, and the third improving still more based on extensive consultation of legacy surveillance records that provided considerable additional information about each case. To illustrate the implications of these seemingly subtle improvements in data quality, we develop ecological niche models and predictive maps of monkeypox transmission risk based on each of the three occurrence data sets.

Rabies surveillance and control measures vary significantly between Caribbean islands. The Centers for Disease Control and Prevention currently recommends certain groups of U.S. travelers to any Caribbean island receive pre-exposure rabies immunization. However, most islands self-declare as “rabies free”, and have never publicly released data to support rabies-free claims. We used the Analytic Hierarchy Process to create pairwise comparison values among five risk factors determined by subject matter experts. Risk factor weights were calculated and used in a geospatial analysis to calculate a risk value for each island nation (higher values indicate higher risk). Risk values ranged from 8.73 (Trinidad) to 1.57 (The Bahamas, Turks and Caicos Islands). All four countries that have documented occurrences of laboratory confirmed rabid bats were ranked highest (Trinidad and Tobago, Grenada, Cuba, Dominican Republic), as well as Haiti. The top five highest risk countries that currently have no reports of bat rabies include St. Vincent and the Grenadines, Jamaica, Puerto Rico, the Cayman Islands, and Dominica. This study reviews the inter-island movement potential of bats, designates areas of high risk for bat-associated rabies within the Caribbean islands, and demonstrates a need for further surveillance efforts in bat populations within islands that self-declare as rabies free.