Here we show that ecological, climatic and landscape factors could predict future hotspots of human viral diseases emergence on a global scale and could thus serve as a basis for surveillances and early warning systems. For the three groups of viral diseases studied, we were able to map areas at high risk of disease emergence based on the spatial distribution of disease reservoirs and hosts as well as WHO data on the distribution of each disease. We found that human-related factors, and in particular the impact of population growth on human-modified landscape, were a common predictor of disease emergence. Filoviridae and henipavirus outbreaks were also linked to rainfall, while Filoviridae and Coronaviridae emergences were favoured by increased in minimum night-time temperature. In addition, for Filoviridae, we noted the potential involvement of “unknown” variables (variables not used in this study). In Africa, these variables could relate to human behaviour, such as bushmeat consumption, biodiversity loss or even other bioclimatic covariates. Interestingly, coronavirus diseases are the only ones to be positively impacted by human population density. Similarly, hotspots of henipaviruses depended on areas of low elevation and low rainfall.
Recent research has shown that increased surface temperature and unpredictable seasonal rainfall due to climate change have an indirect effect on disease emergence through sudden ecological changes of their reservoir, loss of biodiversity and migration of small mammal hosts (García et al., 2018; El-Sayed and Kamel, 2020). For example, minimum temperature is the limiting factor for parasite development and vector distribution in malaria transmission (Patz and Olson, 2006) and other vector-borne disease epidemics such as Crimean Congo Hemorrhagic Fever and Zika (Myers et al., 2013; Broxton et al., 2014). Unfortunately, research outside of vector-borne diseases is limited. However, this direct spatial dependence of disease emergence on minimum temperatures is worrying. Indeed, with climate change, increasing night-time minimum temperatures lengthening the frost-free season in most mid- and high latitude regions (Folland, Karl and Salinger, 2002) could potentially increase the latitudinal extent of infectious disease emergence.
We also found that low elevation and high rainfall have a significant influence on the distribution of Henipavirus outbreaks. Consistent with our results, studies have hypothesized that the emergence of Nipah in the lower Gangetic plains and low-lying marshes could be attributed to flooding, which leads to the destruction of mammalian habitats (Ambat et al., 2019). Rapid changes in ecological habitats due to human land-use change lead to starvation and migration of fruit bat species (Family Pteropodidae), reservoirs of Nipah virus, with contamination of fruit trees near human habitations and increased exposure to the pathogen (JH et al., 2006; Ambat et al., 2019; Royce and Fu, 2020). Our results support this hypothesis of the increased risk of Nipah outbreaks associated with lowland plains, flooding, and rapid human-induced habitat changes.
EVD and coronaviral diseases have also been found to be associated with human-modified landscapes. EVD has long been linked to landscape alterations such as deforestation, mining, population growth and land fragmentation (Castillo-Chavez et al., 2015; Olivero et al., 2017; Redding et al., 2019). Our results show that EVD outbreaks are not directly related to population density, contrary to a recent study (Redding et al., 2019), but rather to the effects of population increase on the human-modified landscape, such as urbanization, deforestation, mining and hunting. In contrast, population density was significantly related to coronavirus hotspots. Whether high population density leads to observer bias and thus to increased reporting of outbreaks needs to be examined in detail. The report of a SARS-like pneumonia in 2012 in miners in the Tongguan, Mojiang (Rahalkar and Bahulikar, 2020) raises the issue of potentially unreported sporadic outbreaks in regions with limited populations. Studies show that the emergence of coronaviral disease such as SARS (Shi and Hu, 2008) and MERS (Dromedaris en ‘Middle East respiratory syndrome’ | Nederlands Tijdschrift voor Geneeskunde, no date) is directly related to exposure to body fluids from mammal raised in confined spaces for bushmeat and recreation activities, respectively. “Wild flavour” bushmeat restaurants and markets are often located in densely populated cites where the demand for exotic proteins is high (Wolfe et al., 2005; Lee et al., 2020) and cases are therefore more likely to be reported in densely populated areas. In the case of MERS, there is an increase in reporting in large cities as camel owners seek treatment for respiratory distress in tertiary hospitals located in large cities and are therefore likely to report cases. The effect of population density is, however, crucial in the spread of the epidemic and therefore remains an important factor in the detection of hotspot and active surveillance.
We suggest here the urgent need of alternatives to rapid land-use changes such as deforestation, land fragmentation for agriculture and livestock, and changes in cultural practices for bushmeat consumption. More importantly, the results highlight the major impact of increasing population and human activities on land alteration and ecological changes, as well as the dependence of viral disease emergences on bioclimatic changes (minimum temperature, rainfall, low elevation and flooded areas) at the global scale. We show the potential of using climatic, topographic and population data to identify and predict areas at high risk of disease emergence. Although our study focused on three viral diseases of concern, we suggest that such biogeographic approach to predicting disease emergence should be considered and tested for other diseases under surveillance in a global active surveillance context.