Bayesian Spatiotemporal Pattern and Eco-climatological Drivers of Striped Skunk Rabies in the North Central Plains

Risk mapping and risk factors analysis of rabies in livestock in Bangladesh using national-level passive surveillance data

Rabies is a major zoonotic disease around the world, causing significant mortality to both humans and animals, especially in low- and middle-income countries. In Bangladesh, rabies is transmitted mostly by the bite of infected dogs and jackals to humans and domestic livestock, causing severe economic losses and public health hazards. Our study analyzed national passive surveillance data of veterinary hospital-reported rabies cases in cattle, buffalo, sheep, and goats from 2015 to 2017 in all 64 districts of Bangladesh. We used a zero-inflated negative binomial regression model to identify the main environmental and socio-economic risk factors associated with rabies occurrence in livestock, and we used model results to generate risk maps. Our study revealed that monsoon precipitation (RR=1.28, p-value=0.043) was positively associated with rabies cases in livestock, and the percentage of adults who have completed university education was also a significant predictor (RR=0.58, p-value<0.001) likely suggesting that districts with higher education levels tended to have a lower reporting of rabies cases in livestock. The standardized incidence ratio maps and predicted relative risk maps revealed a high risk of rabies cases in southeast areas in Bangladesh. We recommend implementing risk-based vaccination strategies in dogs and jackals in those high-risk areas before monsoon to reduce the burden of rabies cases in domestic ruminants and humans in Bangladesh.

Ecological and Socioeconomic Factors in the Occurrence of Rabies: A Forgotten Scenario

In many third world countries, where rabies is endemic in dog populations, humans continue to be at risk of contracting the disease. Vaccination is the most effective form of prophylaxis for people, yet it often fails to adequately protect dogs. The most major implications are the costs of post-exposure prophylaxis (PEP) after an exposure occurs and the loss of human life and productivity due to early mortality from rabies (about 60,000 deaths annually). The largest rabies death tolls can be found in the world's poorest regions, where rabies vaccinations for domestic dogs are uncommon and PEP is scarce. Mass vaccination of dogs, neutering programs, patient PEP, strengthening laboratory and human resources, education and awareness, and animal and human rabies surveillance are all common methods used to prevent, control, and ultimately eradicate dog-mediated human rabies. Current rabies control initiatives, however, pay little attention to the role that ecological and socioeconomic variables play in the disease's occurrence and spread. To help better inform rabies control strategies, we address in this work the ways in which ecological and socioeconomic factors affect the occurrence and spread of rabies.

Spatial and temporal dynamic analysis of rabies: A review of current methodologies

Rabies continues to be one of the deadliest, high risk diseases worldwide, posing a severe threat to public health. The lack of human-to-human transmission means that the spread of rabies is not significantly affected by the distribution of humans or migra- tion. Thus, the spatiotemporal dynamic of cases in both wild and domestic animals is an important issue that can result in human cases. This paper gives an overview of the methodologies for the spatial and temporal dynamic analysis of this disease. It introduces the most representative research progress of spatial aggregation, dynamic transmission, spatiotemporal distribution, epidemiologi- cal analysis and application of modelling in the study of rabies transmission in recent years. This overview should be useful for investigating the spatial and temporal dynamics of rabies, as it could help understanding the spread of cases as well as contribute to the development of better prevention and control strategies in ecology and epidemiology.

Rabies outbreak in black-backed jackals (Canis mesomelas), South Africa, 2016

Rabies, a fatal and vaccine-preventable disease, is endemic throughout Africa. In 2016, a rabies outbreak occurred in black-backed jackals (Canis mesomelas) along the western boundary of Gauteng Province, South Africa. We investigated the possible drivers of the 2016 outbreak and established its origin. Using spatio-temporal locations of cases, we applied logistic regression and Geographic Information System techniques to investigate environmental covariates driving occurrences of emerging rabies cases in Gauteng Province. About 53.8% of laboratory-confirmed lyssaviruses in Gauteng Province in 2016 originated from jackals. Phylogenetic trees reconstructed from a partial region of the glycoprotein gene of these and historical rabies viruses (RABVs) demonstrated the lyssaviruses to be of canid origin with 97.7% nucleotide sequence similarity. The major cluster comprised jackal RABVs from the 2012 KwaZulu/Natal outbreak and the 2016 outbreak in Gauteng Province. The second cluster was composed of both jackal and dog RABVs. Both clusters correlated with independent RABV introductions into Gauteng by dogs and jackals, respectively. This study demonstrated an expansion of a jackal rabies cycle from north-west Province into Gauteng Province during the 2016 dry period, as jackals ranged widely in search for food resources leading to increased jackal-dog interactions, reminiscent of the intricate links of domestic and wildlife rabies cycles in South Africa.

The rabies distribution pattern on dogs using average nearest neighbor analysis approach in the Karangasem District, Bali, Indonesia, in 2019

BACKGROUND AND AIM

Rabies is a severe progressive encephalitis disease in dogs characterized as a zoonosis. The transmission of rabies between animals in Karangasem District, Bali is still high and continues until today; therefore, rabies in the district still actively circulating. The distribution pattern of rabies, especially in the district, is unknown. This research aimed to describe the spatial distribution of rabies in Karangasem District. The information would help in developing effective control strategies for the disease.

MATERIALS AND METHODS

An observational study was carried out using 38 positive rabies cases confirmed by the direct fluorescent antibody test diagnosed at the Disease Investigation Centre of Denpasar from September 2018 to September 2019. The Global Positioning System was used to take the geographical coordinates of the places where positive rabies cases had been confirmed in Karangasem District. The ArcGIS version 10.3 (ESRI) was used to determine and analyze the distribution pattern using the average nearest neighbor (ANN) method.

RESULTS

On the basis of the ANN analysis, the rabies distribution pattern in Karangasem District in 2019 was clustered in groups but not significant (Z-score=-1.670309 [<-1.65], p=0.094858 [<0.1]; nearest neighbor ratio=0.858364). The rabies distribution pattern in each subdistrict of Karangasem was dispersed significantly since it had z-score of more than 2.58, p-value less than 0.1 and nearest neighbor ratio of more than 1.

CONCLUSION

The rabies distribution in Karangasem District had a clustered pattern, although this was not significant. The grouping of rabies in Karangasem District showed a significant dispersed pattern in the subdistricts Abang, Bebandem, and Karangasem. The dispersed pattern of the rabies cases in the subdistricts was caused by unidentified stray dogs that lived in rice fields and other fields and by the whole district's hilly and mountainous topography. The ANN analysis suggested that for rabies control in Karangasem District, vaccination, elimination, and sterilization of stray dogs should be conducted in densely populated areas.

The impact of anthropogenic and environmental factors on human rabies cases in China

Human rabies is a public health problem in Asia, especially in less-developed regions where the disease is under-reported because of a lack of epidemiological surveillance. To address this gap, we collected data on human rabies in Yunnan Province, China, between 2005 and 2016. Using statistical mapping techniques, we correlated the occurrence of human rabies to environmental (elevation, precipitation, normalized difference vegetation index [NDVI], temperature and distance to the nearest main rivers) and anthropogenic (human and dog population density, distance to the nearest main roads and gross domestic product [GDP]) factors. We used a performance score, the average area under the receiver operator characteristic curve (0.88), to validate our risk model. Using this model, we found that environmental factors were more strongly associated with human rabies occurrence than anthropogenic factors. Areas with elevation below 2000 metres, GDP per capita between $750 and $4500/year and NDVI below 0.07 were associated with greater risk of human rabies. Rabies control in China should specifically target these areas.

Diarrhea Patterns and Climate: A Spatiotemporal Bayesian Hierarchical Analysis of Diarrheal Disease in Afghanistan

Subject to a high burden of diarrheal diseases, Afghanistan is also susceptible to climate change. This study investigated the spatiotemporal distribution of diarrheal disease in the country and how associated it is with climate variables. Using monthly aggregated new cases of acute diarrhea reported between 2010 and 2016 and monthly averaged climate data at the district level, we fitted a hierarchical Bayesian spatiotemporal statistical model. We found aridity and mean daily temperature were positively associated with diarrhea incidence; every 1°C increase in mean daily temperature and 0.01-unit change in the aridity index were associated with a 0.70% (CI: 0.67%, 0.73%) increase and a 4.79% (CI: 4.30%, 5.26%) increase in the risk of diarrhea, respectively. Average annual temperature, on the other hand, was negatively associated, with a 3.7% (CI: 3.74%, 3.68) decrease in risk for every degree Celsius increase in annual average temperature. Temporally, most districts exhibited similar seasonal trends, with incidence peaking in summer, except for the eastern region where differences in climate patterns and population density may be associated with high rates of diarrhea throughout the year. The results from this study highlight the significant role of climate in shaping diarrheal patterns in Afghanistan, allowing policymakers to account for potential impacts of climate change in their public health assessments.

Spatiotemporal Distribution of Hand, Foot, and Mouth Disease in Guangdong Province, China and Potential Predictors, 2009⁻2012

Background: Hand, foot, and mouth disease (HFMD) is a common infectious disease among children. Guangdong Province is one of the most severely affected provinces in south China. This study aims to identify the spatiotemporal distribution characteristics and potential predictors of HFMD in Guangdong Province and provide a theoretical basis for the disease control and prevention. Methods: Case-based HFMD surveillance data from 2009 to 2012 was obtained from the China Center for Disease Control and Prevention (China CDC). The Bayesian spatiotemporal model was used to evaluate the spatiotemporal variations of HFMD and identify the potential association with meteorological and socioeconomic factors. Results: Spatially, areas with higher relative risk (RR) of HFMD tended to be clustered around the Pearl River Delta region (the mid-east of the province). Temporally, we observed that the risk of HFMD peaked from April to July and October to December each year and detected an upward trend between 2009 and 2012. There was positive nonlinear enhancement between spatial and temporal effects, and the distribution of relative risk in space was not fixed, which had an irregular fluctuating trend in each month. The risk of HFMD was significantly associated with monthly average relative humidity (RR: 1.015, 95% CI: 1.006–1.024), monthly average temperature (RR: 1.045, 95% CI: 1.021–1.069), and monthly average rainfall (RR: 1.004, 95% CI: 1.001–1.008), but not significantly associated with average GDP. Conclusions: The risk of HFMD in Guangdong showed significant spatiotemporal heterogeneity. There was spatiotemporal interaction in the relative risk of HFMD. Adding a spatiotemporal interaction term could well explain the change of spatial effect with time, thus increasing the goodness of fit of the model. Meteorological factors, such as monthly average relative humidity, monthly average temperature, and monthly average rainfall, might be the driving factors of HFMD.

Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public

Background

Prevention and control of wildlife disease invasions relies on the ability to predict spatio-temporal dynamics and understand the role of factors driving spread rates, such as seasonality and transmission distance. Passive disease surveillance (i.e., case reports by public) is a common method of monitoring emergence of wildlife diseases, but can be challenging to interpret due to spatial biases and limitations in data quantity and quality.

Methodology/Principal findings

We obtained passive rabies surveillance data from dead striped skunks (Mephitis mephitis) in an epizootic in northern Colorado, USA. We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. We estimated the distance travelled per transmission event, direction of invasion, rate of spatial spread, and effects of infection density and season. We also estimated mean transmission distance and rates of spatial spread using a phylogeographic approach on a subsample of viral sequences from the same epizootic. Both the occupancy and phylogeographic approaches predicted similar rates of spatio-temporal spread. Estimated mean transmission distances were 2.3 km (95% Highest Posterior Density (HPD₉₅): 0.02, 11.9; phylogeographic) and 3.9 km (95% credible intervals (CI₉₅): 1.4, 11.3; occupancy). Estimated rates of spatial spread in km/year were: 29.8 (HPD₉₅: 20.8, 39.8; phylogeographic, branch velocity, homogenous model), 22.6 (HPD₉₅: 15.3, 29.7; phylogeographic, diffusion rate, homogenous model) and 21.1 (CI₉₅: 16.7, 25.5; occupancy). Initial colonization probability was twice as high in spring relative to fall.

Conclusions/Significance

Skunk-to-skunk transmission was primarily local (< 4 km) suggesting that if interventions were needed, they could be applied at the wave front. Slower viral invasions of skunk rabies in western USA compared to a similar epizootic in raccoons in the eastern USA implies host species or landscape factors underlie the dynamics of rabies invasions. Our framework provides a straightforward method for estimating rates of spatial spread of wildlife diseases.

Rabies is a deadly zoonotic infection with a global distribution. In 2012, an epizootic of skunk rabies established in northern Colorado, USA and spread rapidly through three counties. The epizootic was documented through reports of dead skunks by the public. We examined the reports to determine how rapidly rabies was moving and which factors could explain the patterns of spread. We compared these estimates of spatial movement of rabies to those obtained from analyzing rabies genetic sequences that we obtained from some of the dead skunks reported by the public. By both methods, we found the virus was moving south at a little over 20 km/year and that most transmission between skunks occurred at short distances (< 4 km). Rabies was most likely to spread to new areas during the first half of the year, when skunk populations were producing new offspring. Our genetic model suggested that roads and rivers in the study landscape did not affect movement speed of rabies. We developed a framework that used the spatial data in the public reports to predict where and when skunk rabies would occur next. This framework could be used on public health surveillance data for other diseases or countries.

Management and modeling approaches for controlling raccoon rabies: The road to elimination

Rabies is an ancient viral disease that significantly impacts human and animal health throughout the world. In the developing parts of the world, dog bites represent the highest risk of rabies infection to people, livestock, and other animals. However, in North America, where several rabies virus variants currently circulate in wildlife, human contact with the raccoon rabies variant leads to the highest per capita population administration of post-exposure prophylaxis (PEP) annually. Previous rabies variant elimination in raccoons (Canada), foxes (Europe), and dogs and coyotes (United States) demonstrates that elimination of the raccoon variant from the eastern US is feasible, given an understanding of rabies control costs and benefits and the availability of proper tools. Also critical is a cooperatively produced strategic plan that emphasizes collaborative rabies management among agencies and organizations at the landscape scale. Common management strategies, alone or as part of an integrated approach, include the following: oral rabies vaccination (ORV), trap-vaccinate-release (TVR), and local population reduction. As a complement, mathematical and statistical modeling approaches can guide intervention planning, such as through contact networks, circuit theory, individual-based modeling, and others, which can be used to better understand and predict rabies dynamics through simulated interactions among the host, virus, environment, and control strategy. Strategies derived from this ecological lens can then be optimized to produce a management plan that balances the ecological needs and program financial resources. This paper discusses the management and modeling strategies that are currently used, or have been used in the past, and provides a platform of options for consideration while developing raccoon rabies virus elimination strategies in the US.