High-resolution forest data from satellites are available since the year 200030. To allow evaluation of changes in forest cover and forest fragmentation prior to each outbreak, we consider events of first reported Ebolavirus infections in humans (index cases) that occurred after 2004. We identify eleven independent index cases (Table 1)8,31: i.e., presumed primary infection events due to spillover from wildlife reservoirs to humans in the study region (triangles in Fig. 1). Using existing 30 m high-resolution tree cover data30, we find that on the outbreak year (Table 1) the average forest cover in the surroundings of these eleven centers of first infection (e.g., within a 25 or 50 km radius) was significantly greater than the average forest cover across the region (p-value 0.0052 and 0.0301; see Tables 2 and S1). While the centers of first infection are not preferentially located in hotspots of forest loss (Tables 2 and S2), they tend to occur in areas where on the outbreak year the average degree of forest fragmentation (e.g., within a 25 km, 50 km or 100 km distance from the infection center) was significantly higher (p-values 0.0062, 0.0047 and 0.0072, respectively) than in the rest of the region (Table S3). We analyzed forest fragmentation, in this study expressed in terms of a compound fragmentation index, CFI, defined as the fraction of the landscape covered with forest margin sites or with smaller (<200 ha) forest fragments (see Methods). Forest fragmentation (i.e., CFI) on average increases with decreasing distance from the center of infection (Figure S1 and Table S3). Likewise, the increase in forest fragmentation (between 2000 and the infection year) was on average stronger in areas close to the infection centers (Table S4). Within 25 km from the centers of first infection changes in forest fragmentation between 2000 and the infection year were on average positive (Table S4) and significantly greater than the average increase (2000–2014) in forest fragmentation across the region. These p-value estimates are conservative because, while in the infection areas changes in forest cover and fragmentation were evaluated between 2000 (baseline year) and time of infection, regional changes were determined using a longer period (2000–2014) during which fragmentation has increased across the region (Tables 2 and S2, S4). These results, however, could be affected by a bias because areas that are more populated are more likely to exhibit both enhanced contact between infection reservoir and humans and forest fragmentation by land use change29. Using spatially extended population data (see Methods), we find that population density within 25 km from the (presumed) first infection points is indeed significantly greater than across the region (p-value 0.0117) (Table 2). To remove the bias associated with higher population density, we compare forest cover, loss, and fragmentation between the areas surrounding the 11 centers of first infection (e.g., 25 km radius), and randomly selected areas (hereafter called IQR areas) with 25 km radius and population density comprised within the interquartile range (IQR) of the population in the areas of first infection. Interestingly, we found that while the mean population density within 25 km from the 11 centers of first infection and across the randomly selected IQR areas were not significantly different (p-value 0.5766), a significant difference existed in forest cover (p-value 0.0001), forest fragmentation (p-value 0.0318) and change in fragmentation (p-value 0.0033) between 2000 and the infection year. Similar level of significance are obtained when only sites of first infection of Central Africa are considered. Thus, sites of first infection on average exhibit significantly higher population density (Table 2), average forest cover (Tables 2 and S1), fragmentation and increase in fragmentation (Tables 2 and S3, S4) than the rest of the region. These findings are robust with respect to possible biases associated with non-uniform population densities. Interestingly, outbreaks occurred more often in forested areas affected by fragmentation, when considering areas with similar population density. Thus, even though the rates of forest loss in the areas of first infection are not significantly greater than those observed across the region as a whole, our results indicate that Ebolavirus spillover events from wildlife reservoirs to humans preferentially occur in areas that are relatively populated and forested, yet where deforestation is reshaping the forest boundaries by increasing forest fragmentation29. We recognize that since humans may travel long distances, the site of the first reported (index) case of EVD in an outbreak does not necessarily coincide with the site of first infection. For this reason, a neighborhood within a distance of at least 25 km was considered for each presumed center of first infection.

Table 1 Centers of first infection of Ebola virus disease in humans (data from refs 8,31). Full size table

Table 2 Average forest cover, forest loss, fragmentation (CFI), and change in fragmentation in the surroundings of centers of first infection and across the region. Full size table

We also use the Getis-Ord analysis (see Methods) to determine whether the centers of first infection are hotspots of forest fragmentation and find (Table S3) that 8 out of the 11 infection events included in this study took place in fragmentation hotspots identified with confidence levels ranging between 90% and 99%. The three exceptions are the outbreaks of Yambio (Fig. 2 – event n. 1), which falls, however, very close (≈80 km) to a high fragmentation NW-SE corridor (Figure S2), and Odzala and Inkanamongo (Fig. 2 – events n. 2 and 11), the former associated with hunting/poaching activities in the forest and for which the source species remains uncertain32. Interestingly, both index cases 2 and 11 were reportedly thought to be infected while hunting small animals for food.

Overall our results are consistent with the notion that the transmission of ebolaviruses to human populations is more likely to occur in highly disturbed forested areas. Though it is unlikely that deforestation overall improves the habitat of bat species, ‘edge effects’ as a result of habitat fragmentation have been linked to a reduction in insectivorous and increase in frugivorous bat abundance in numerous studies33,34,35,36. In a recent systematic review of responses of tropical bats to habitat fragmentation, logging, and deforestation37 only two studies out of 117 were from Africa, precluding any analysis. One generality from this meta-analysis, however, was that frugivorous tropical bats often increase in fragmented habitats, though the studies were typically from the Neotropics38,39,40. In the absence of virus isolation from bats there is no conclusive evidence that bat species are the natural reservoirs for ebolaviruses and factors controlling the mechanisms of spillover to humans remain poorly understood8,12. However, our results are robust to any specific assumption on reservoir hosts, provided that the reservoir host is a forest dwelling wild species. While the reservoir hosts for ebolaviruses are still uncertain (see ref. 10,12), several index human cases of EVD, particularly in Gabon, had been linked to contact with Ebola virus infected apes (e.g. Gabon, 1996, 2001–2003, refs 41, 42, 43). Interestingly 64 animal carcasses were within a 2-hour walking distance of villages, including 22 gorillas (13 positive), eight chimpanzees (four positive), and six duikers (one positive)42. Furthermore, the impact of fragmentation and habitat use on these species is better studied than on bats. For example, following disturbance through logging in northern Republic of Congo, gorilla, chimpanzee and duiker densities initially decline but can all increase in density with time, sometimes exceeding pre-disturbance densities depending on the species44. Duiker more quickly increase in abundance peaking around 10 years post disturbance then decline, whereas chimpanzees and gorillas have been recorded to steadily increase with time over 30 years periods44. Together these studies suggest that habitat fragmentation facilitate EVD outbreaks as it may lead to increased contact between humans as they encroach and potent Ebolavirus reservoirs. Thus, fragmented forest edges could be preferential corridors for pathogen transmission from wildlife reservoirs to humans and thereby favor the emergence of some zoonotic infections7.

High degrees of forest fragmentation and their increase over time can be good indicators of enhanced opportunities for human contact with wildlife because of human penetration in wildlife habitat and, possibly, also improved habitat for some reservoir species5,13,33,34,35,36,45. In fact, while wildlife virus hosts vary in their sensitivity to habitat disturbance, the specific African bat species with the strongest evidence for being filovirus hosts (Rousettus aegyptiacus [for Marburgvirus], and Hypsignathus monstrosus, Epomops franqueti, and Myonycteris torquata [for Ebolavirus]) appear to exhibit a broad habitat tolerance46. Indeed, two of the putative Ebola virus hosts (i.e., M. torquata and E. franqueti) are often associated with primary and secondary forests as well as forest-grassland mosaic habitats46. Likewise, as noted above, gorilla, chimpanzee and duiker have been observed to increase in abundance after forest disturbance. Thus, it could be argued that while disturbance by deforestation destroys the habitat of specialist species, generalists – possibly including reservoirs of some zoonotic pathogens – thrive4,5,6, thereby further enhancing the risk of infection in human populations close to the forest margins. The preferential occurrence of first infection events in areas with fragmented forests suggests that fragmentation enhances the contacts between humans and infectious disease vectors with no major loss of some putative host species’ habitat.

While this work has shown the existence of significant relationships between forest fragmentation and areas of ebolavirus spillover to human populations, we can only speculate on the underlying mechanisms (exposure to wildlife, bushmeat consumption, habitat destruction, biodiversity loss). The fact that spillover tends to occur in hotspots of forest fragmentation rather than in clearcut areas suggests that chances of human interactions with host wildlife are higher in areas where human encroachment leaves forest fragments that provide habitat for reservoir species.

Does the notion of increased contacts with wildlife imply that human settlements are moving closer to the forest margins? Our analysis based on maps of populated areas (i.e., settlements) available for Central Africa (see Methods section) shows that the average distance between human settlements and both forest margins, which include edge, perforated, patch sites, and smaller forest cores (<200 ha, see Methods) and larger forest cores (>200 ha), has increased between 2000 and 2014 (Table S5), indicating that the ongoing increase in forest loss and fragmentation is associated with a shift of the forest margins away from human settlements rather than the encroachment of villages and inhabited areas into the forest.

The impact of forest loss on ecosystems and the services they provide is often evaluated in terms of habitat destruction, losses of biodiversity, carbon stock and emissions, land degradation, or altered climate and hydrologic conditions16,47,48. This study, however, highlights that deforestation and forest fragmentation potentially have another important class of externalities associated with global health and zoonotic disease outbreaks15,16,49. These externalities should be accounted for while evaluating the costs, risks, and benefits of human encroachment in forested areas. It is also important to understand the interactions existing among the unwanted effects of forest loss and fragmentation; for instance, biodiversity losses may enhance the likelihood of zoonotic infections through increasing the abundance of some species and thus the infection prevalence of specific pathogens through increased intra-specific host contacts and infection transmission50. By reshaping forest boundaries, altering habitat and reducing biodiversity51,52, the growing global pressure on land and its products is increasing the risk of zoonotic infections with important impacts on human health worldwide53.