Urbanization and Habitat Characteristics Associated with the Occurrence of Peste des Petits Ruminants in Africa

Abstract

As a highly contagious viral disease, peste des petits ruminants (PPR) can cause severe socio-economic impacts in developing countries due to its threat to sheep and goat production. Previous studies have identified several risk factors for PPR at the individual or herd level. However, only a few studies explored the impacts of landscape factors on PPR risk, particularly at a regional scale. Moreover, risk factor analyses in Africa usually focused on sub-Saharan Africa while neglecting northern Africa. Based on regional occurrence data during 2006–2018, we here explored and compared the risk factors, with a focus on factors related to ruminant habitats, for the occurrence of PPR in sub-Saharan and northern Africa. Our results demonstrated different risk factors in the two regions. Specifically, habitat fragmentation was negatively correlated with PPR occurrence in sub-Saharan Africa, while positively correlated with PPR occurrence in northern Africa. Moreover, urbanization showed a positive association with PPR occurrence in sub-Saharan Africa. Our study is among the first, to our knowledge, to compare the risk factors for PPR in sub-Saharan and northern Africa and contributes to a better understanding of the effects of habitat characteristics on PPR occurrence at a regional scale.

Analysis of spatial and temporal risk of Peste des Petits Ruminants Virus (PPRV) outbreaks in endemic settings: A scoping review

“…Most studies (71.2%, n = 30) described the temporal trends of PPR epidemics aggregated per day, week, month or year depending on the temporal aggregation of the original data. Generalized Linear Negative Binomial Regression Model (GLNBRM), (11), Generalized Linear Mixed Models (GLMMs) (47), Negative Binomial (45), linear (15,37,48,49) or logistic regression (50,51) models were used to explore or test hypothesis related to temporal trends. Other studies resorted to Bayesian approaches (3,52,53).…”

“…By including covariates that reflect the circulation of PPRV in wildlife reservoirs like saiga goats, an epidemiological connection between PPRV in wildlife and disease outbreaks in livestock was investigated. For example, closeness to protected, national parks or forest coverage were included in seven analyses (four in Africa and three in Asia) as a representation of a potential livestock–wildlife interaction; among these studies, four reported a positive association between presence or closeness to a protected area and PPR outbreak occurrence; however, this relationship varied across study periods, and locations (11,43,47,57,62,63,69). In general, 47.4% (7/19) of research done in Asia and Africa linked this category of wildlife-livestock interaction to PPR risk.…”

“…Data visualization and descriptions were used by 34 studies (80.9%), and this was the most reliable method used by all the studies to present the distribution of PPR epidemics (55). Various analytical approaches used for data visualization and description include GLMNB (11), GLMMs (47) and negative binomial to assess the potential risk factors associated with the case count of PPR disease from each outbreak. (45,60).…”

“…Poor animal health and veterinary services assessed in Mandi City, northwest of India, have increased the risk of PPR infection (43). The contribution of the urban population to PPR epidemics was reported by two studies, one in Africa and the other in Asia (43,47).…”

“…For instance, in Bangladesh, the livestock movement within herds and the central market of the local small and large markets has been connected to the PPR outbreak (46). Another model which evaluates urbanization and habitat characteristics has shown naked evidence to PPR risk to livestock trade (47). Urban areas are endowed with different level of improved Livestock trade infrastructure (transportation network and slaughter facilities) varied in different regions.…”