Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria

Abstract

The reemergence of monkeypoxvirus (MPXV) in 2017 after about 39 years of no reported cases in Nigeria, and the recent incidence in countries such as the United States of America, United Kingdom, Singapore, and Israel which have been reportedly linked with travelers from Africa, have heightened concern that MPXV may have emerged to occupy the vacant ecological and immunological niche created by the extinct smallpox virus. This study was carried out to identify environmental conditions and areas that are environmentally suitable (risky areas) for MPXV in southern Nigeria. One hundred and sixteen (116) spatially unique MPXV occurrence data from 2017–2021 and corresponding environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of the viral disease. A variance inflation analysis was adopted to limit the number of environmental variables and minimize multicollinearity. The five variables that contributed to the suitability model for MPXV disease are precipitation of driest quarter (47%), elevation (26%), human population density (17%), minimum temperature in December (7%), and maximum temperature in March (3%). For validation, our model had a high AUC value of 0.92 and standard deviation of 0.009 indicating that it had excellent ability to predict the suitable areas for monkeypox disease. Categorized risk classes across southern states was also identified. A total of eight states were predicted to be at high risk of monkeypox outbreak occurrence. These findings can guide policymakers in resources allocation and distribution to effectively implement targeted control measures for MPXV outbreaks in southern Nigeria.

Monkeypox outbreaks in the context of the COVID-19 pandemic: Network and clustering analyses of global risks and modified SEIR prediction of epidemic trends

“…In a third consideration, MPXV and the smallpox virus are both orthopoxviruses and have cross-immunity with one another ( 22 ); with the vaccination against smallpox having been phased out globally around 1980, people under the age of 40 worldwide are likely to be at high risk of MPX infection ( 23 , 24 ). Finally, MPX has repeatedly shown associations with demographic characteristics ( 23 ), forest cover ( 1 , 25 ), temperature ( 1 ), precipitation ( 25 – 27 ), socioeconomic factors ( 28 , 29 ), biodiversity ( 30 ), and health-associated factors, which are also potential risk factors for most infectious diseases.…”

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

“…Next, the least contributing and high standard deviation (SD) 20,21 variables were eliminated stepwise and using the MaxEnt model. 21,22 Finally, variance inflation factor (VIF) 23,24 analysis was conducted to evaluate the multicollinearity among predictors after the reduction. 25 A VIF value below 10 indicates low and acceptable multicollinearity.…”

Modeling the current and future distribution of Brucellosis under climate change scenarios in Qinghai Lake basin, China

“…The ideal fi ltering or thinning process keeps the occurrence points with the most insightful data while simultaneously Fig ure 1. Study area: Qinghai Lake basin in Qinghai Province, People's Republic of China removing the fewest records required to signifi cantly lessen the impacts of sampling bias [37]. The occurrence points were then stored as comma-separated values (CSV) and imported into ArcGIS (version 10.6 ESRI) for editing.…”