A cointegration analysis of rabies cases and weather components in Davao City, Philippines from 2006 to 2017

PLoS One. 2020 Aug 25;15(8):e0236278. doi: 10.1371/journal.pone.0236278. eCollection 2020.

Abstract

Rabies is a lethal viral disease and dogs are the major disease reservoir in the Philippines. Spatio-temporal variations in environmental factors are known to affect disease dynamics. Some rabies-affected countries considered investigating the role of weather components in driving rabies cases and it has helped them to strategize their control efforts. In this study, cointegration analysis was conducted between the monthly reported rabies cases and the weather components, such as temperature and precipitation, to verify the effect of weather components on rabies incidence in Davao City, Philippines. With the Engle-Granger cointegration tests, we found that rabies cases are cointegrated into each of the weather components. It was further validated, using the Granger causality test, that each weather component predicts the rabies cases and not vice versa. Moreover, we performed the Johansen cointegration test to show that the weather components simultaneously affect the number of rabies cases, which allowed us to estimate a vector-error correction model for rabies incidence as a function of temperature and precipitation. Our analyses showed that canine rabies in Davao City was weather-sensitive, which implies that rabies incidence could be projected using established long-run relationship among reported rabies cases, temperature, and precipitation. This study also provides empirical evidence that can guide local health officials in formulating preventive strategies for rabies control and eradication based on weather patterns.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Causality
  • Cities / statistics & numerical data
  • Datasets as Topic
  • Disease Reservoirs / virology*
  • Dogs / virology*
  • Ecological Parameter Monitoring / statistics & numerical data*
  • Forecasting / methods
  • Humans
  • Incidence
  • Models, Statistical
  • Philippines / epidemiology
  • Rabies / epidemiology*
  • Rabies / prevention & control
  • Rabies / virology
  • Rabies virus
  • Spatio-Temporal Analysis
  • Weather*

Grant support

All authors are funded by the Commission on Higher Education of the Philippines with Discovery Applied Research and Extension for Trans/Inter-disciplinary Opportunities (CHED DARE-TO) 2017 Research Grant through the Synoptic Study on Transmission and Optimum Control to Prevent (STOP) Rabies Research Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.