Using remote sensing to map the risk of human monkeypox virus in the Congo Basin

Abstract

Although the incidence of human monkeypox has greatly increased in Central Africa over the last decade, resources for surveillance remain extremely limited. We conducted a geospatial analysis using existing data to better inform future surveillance efforts. Using active surveillance data collected between 2005 and 2007, we identified locations in Sankuru district, Democratic Republic of Congo (DRC) where there have been one or more cases of human monkeypox. To assess what taxa constitute the main reservoirs of monkeypox, we tested whether human cases were associated with (i) rope squirrels (Funisciurus sp.), which were implicated in monkeypox outbreaks elsewhere in the DRC in the 1980s, or (ii) terrestrial rodents in the genera Cricetomys and Graphiurus, which are believed to be monkeypox reservoirs in West Africa. Results suggest that the best predictors of human monkeypox cases are proximity to dense forests and associated habitat preferred by rope squirrels. The risk of contracting monkeypox is significantly greater near sites predicted to be habitable for squirrels (OR = 1.32; 95% CI 1.08-1.63). We recommend that semi-deciduous rainforests with oil-palm, the rope squirrel's main food source, be prioritized for monitoring.

Figure 1

Sankuru district, Democratic Republic of Congo. Main panel: Sankuru’s major towns and roads. Inset: The regional context of monkeypox epidemics in Central Africa. Since 1970, the largest number of human monkeypox cases has been reported in the Congo River basin in the Democratic Republic of Congo (DRC), but monkeypox has recently been identified in the Republic of Congo (ROC) and Sudan. The gray polygon in the central DRC is the Sankuru district

Figure 2

Georeferenced human monkeypox cases in Sankuru (2005–2007). Cases occur predominantly in human settlements located near closed-canopy, semi-deciduous or evergreen forest. These data represent the cases detected through active surveillance for which latitudes and longitudes were available. There are 156 sites, at the 1 km² scale, with at least one confirmed case of human monkeypox. This spatial resolution was chosen so that our analysis would approximate the scale of individual villages, but the processing of the satellite images would remain computationally tractable. Such processing becomes more difficult with an increasingly fine scale

Figure 3

Stages of the analysis. The ecological variables were measured by analyzing satellite images of Sankuru (for an overview of this methodology, see Jensen, 2007). Section 1.7 of the Supplementary Material describes the model validation. MPX, monkeypox; PCA, principal components analysis

Figure 4

Different modeling approaches provide similar predictions about the geographic distribution of human monkeypox (MPX) in Sankuru. The polygons outlined in gray are subdistricts within Sankuru. Section 1.7 of the Supplementary Material describes how we quantified the degree of similarity between logistic regression and Maxent

Figure 5

Risk maps of human monkeypox in Sankuru. (a) Probability that sites in Sankuru are in the ecological niche of monkeypox (MPX), according to the logistic regression model. Figure 4 shows the predicted probabilities prior to the application of the 0.5 threshold. (b) Human population per km². The polygons outlined in black are subdistricts within Sankuru. (c) Human population density overlaid on ecological suitability for the virus. “MPX High” means the probability of an MPX case is estimated to be greater than 0.5. Sites with human population densities greater than 10 people/km² are labeled “Pop High.” Defining “High” and “Low” using other thresholds gave similar results