Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria

Author:

Arotolu Temitope Emmanuel,Afe Ayoola Ebenezer,Wang HaoNing,Lv JiaNing,Shi Kun,Huang LiYa,Wang XiaoLongORCID

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.

Funder

State Key Laboratory of Veterinary Biotechnology Foundation

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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