In response to: "Increased dog population and potential for bat-borne rabies spillover in Chile in response to "Dog management, abundance and potential for bat-borne rabies spillover in Chile" by Astorga et al. [Prev. Vet. Med. 118:397-405]" by Acosta-Jammet, G

Urban dogs in rural areas: Human-mediated movement defines dog populations in southern Chile

Management strategies for dog populations and their diseases include reproductive control, euthanasia and vaccination, among others. However, the effectiveness of these strategies can be severely affected by human-mediated dog movement. If immigration is important, then the location of origin of dogs imported by humans will be fundamental to define the spatial scales over which population management and research should apply. In this context, the main objective of our study was to determine the spatial extent of dog demographic processes in rural areas and the proportion of dogs that could be labeled as immigrants at multiple spatial scales. To address our objective we conducted surveys in households located in a rural landscape in southern Chile. Interviews allowed us to obtain information on the demographic characteristics of dogs in these rural settings, human influence on dog mortality and births, the localities of origin of dogs living in rural areas, and the spatial extent of human-mediated dog movement. We found that most rural dogs (64.1%) were either urban dogs that had been brought to rural areas (40.0%), or adopted dogs that had been previously abandoned in rural roads (24.1%). Some dogs were brought from areas located as far as ∼700km away from the study area. Human-mediated movement of dogs, especially from urban areas, seems to play a fundamental role in the population dynamics of dogs in rural areas. Consequently, local scale efforts to manage dog populations or their diseases are unlikely to succeed if implemented in isolation, simply because dogs can be brought from surrounding urban areas or even distant locations. We suggest that efforts to manage or study dog populations and related diseases should be implemented using a multi-scale approach.

Advances and Limitations of Disease Biogeography Using Ecological Niche Modeling

Mapping disease transmission risk is crucial in public and animal health for evidence based decision-making. Ecology and epidemiology are highly related disciplines that may contribute to improvements in mapping disease, which can be used to answer health related questions. Ecological niche modeling is increasingly used for understanding the biogeography of diseases in plants, animals, and humans. However, epidemiological applications of niche modeling approaches for disease mapping can fail to generate robust study designs, producing incomplete or incorrect inferences. This manuscript is an overview of the history and conceptual bases behind ecological niche modeling, specifically as applied to epidemiology and public health; it does not pretend to be an exhaustive and detailed description of ecological niche modeling literature and methods. Instead, this review includes selected state-of-the-science approaches and tools, providing a short guide to designing studies incorporating information on the type and quality of the input data (i.e., occurrences and environmental variables), identification and justification of the extent of the study area, and encourages users to explore and test diverse algorithms for more informed conclusions. We provide a friendly introduction to the field of disease biogeography presenting an updated guide for researchers looking to use ecological niche modeling for disease mapping. We anticipate that ecological niche modeling will soon be a critical tool for epidemiologists aiming to map disease transmission risk, forecast disease distribution under climate change scenarios, and identify landscape factors triggering outbreaks.

Forecasting Chikungunya spread in the Americas via data-driven empirical approaches

BACKGROUND

Chikungunya virus (CHIKV) is endemic to Africa and Asia, but the Asian genotype invaded the Americas in 2013. The fast increase of human infections in the American epidemic emphasized the urgency of developing detailed predictions of case numbers and the potential geographic spread of this disease.

METHODS

We developed a simple model incorporating cases generated locally and cases imported from other countries, and forecasted transmission hotspots at the level of countries and at finer scales, in terms of ecological features.

RESULTS

By late January 2015, >1.2 M CHIKV cases were reported from the Americas, with country-level prevalences between nil and more than 20 %. In the early stages of the epidemic, exponential growth in case numbers was common; later, however, poor and uneven reporting became more common, in a phenomenon we term "surveillance fatigue." Economic activity of countries was not associated with prevalence, but diverse social factors may be linked to surveillance effort and reporting.

CONCLUSIONS

Our model predictions were initially quite inaccurate, but improved markedly as more data accumulated within the Americas. The data-driven methodology explored in this study provides an opportunity to generate descriptive and predictive information on spread of emerging diseases in the short-term under simple models based on open-access tools and data that can inform early-warning systems and public health intelligence.