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.

The COVID-19 pandemic has become a public health crisis in the Philippines and the attention of national and local health authorities is focused on managing the fluctuating COVID-19 cases. This study presents a method that integrates risk management tools into health care decision-making processes to enhance the understanding and utilization of risk-based thinking in public health decision making. The risk assessment consists of the identification of the key risk factors of the COVID-19 contagion via bow-tie diagrams. Second, the safety controls for each risk factor relevant to the Davao City context are taken into account and are identified as barriers in the bow-tie. After which, the prioritization of the identified COVID-19 risks, as well as the effectiveness of the proposed interventions, is performed using the analytic hierarchy process. Consequently, the dynamics of COVID-19 management initiatives were explored using these priorities and a system of ordinary differential equations. Our results show that reducing the number of COVID-19 fatalities should be the top priority of the health authorities. In turn, we predict that the COVID-19 contagion can be controlled and eliminated in Davao city in three-month time after prioritizing the fatalities. In order to reduce the COVID-19 fatalities, health authorities should ensure an adequate number of COVID-ready ICU facilities. The general public, on the other hand, should follow medical and science-based advice and suspected and confirmed COVID-19 patients should strictly follow isolation protocols. Overall, an informed decision-making is necessary to avoid the unwanted consequences of an uncontrolled contagion.

Davao City, the largest city in the Philippines with 11 legislative districts, is among the top cities with high rabies incidence. To eliminate the rabies incidence, the City Veterinarian’s Office (CVO) has been implementing the Intensified Rabies Control Program (IRCP) that is composed of mass dog vaccination, dog neutering, dog impounding, and information and education campaigns (IEC). In this paper, we formulated a linear programming (LP) model that minimizes the IRCP operational cost while satisfying the different targets set by the CVO for each of the IRCP component as well as its allocated budget. From the analysis, the CVO should be lessening the number of dogs to be vaccinated in districts whose vaccine coverage is already above 70%. This is to ensure that the number of dogs to be vaccinated in other districts can be increased and achieve 70% vaccine coverage. However, the model suggests that it is optimal that 90% of the dogs in the Talomo district (the most populous district in the city) should be vaccinated. Furthermore, with the 24:1 ratio of the number of vaccinated dogs to the impounded dogs, it is optimal to neuter one dog for every 239 vaccinated dogs. Additionally, the model suggests impounding more dogs to highly populated districts. Lastly, the model suggests maintaining the average number of IEC participants. By doing these interventions firmly, dogs in Davao City can potentially achieve herd immunity, and the human’s risk to contract rabies will be lowered.

IntroductionIn the Philippines, scheduling the COVID-19 vaccine rollout has been a challenging task. The local government units (LGUs) have to carefully work with limited resources to avoid underutilizing vaccines while considering prioritization schemes in the rollout. As the country continues to vaccinate its population to manage the spread of COVID-19, planning the prioritization of individuals becomes more apparent in the vaccination rollout with respect to the COVID-19 situation in their respective areas.MethodsOur study develops a location-allocation model that aims to optimally schedule the COVID-19 vaccine rollout of a municipality. Here we applied the analytic hierarchy process (AHP) to determine the prioritization of communities (i.e., barangays) in the vaccine rollout based on the number of COVID-19 cases, the population density, and the proximity of the community to the available vaccine sites. Consequently, an integer programming (IP) model was formulated to determine the assignment of individuals to the vaccine stations with respect to the prioritization of their community in the rollout, as well as the minimum number of vaccine stations to open.Results and discussionThe AHP-based IP model proposed in this study not only assigns individuals to vaccination centers, but is also capable of tailoring the vaccine rollout to prioritize individuals depending on the preferences of the LGUs, and the COVID-19 situation in their areas. Furthermore, the vaccine rollout framework in this work is applicable to other vaccine-preventable diseases (e.g., rabies, measles, etc.) should LGUs embark on adapting this approach.