ABSTRACT
According to the World Health Organization (WHO), the elderly and people with comorbidities are most vulnerable to COVID-19 infection. With this, the challenges and threats posed to the vulnerable population require targeted interventions. While public health surveillance methods had developed recent advances to meet users' information needs, the volume and complexity of infectious disease data had increased, resulting in increasing difficulty to facilitate risk communication with the public and for decision-makers to make informed measures to protect the public's health. Moreover, the implementation of COVID-19 spatiotemporal disease surveillance strategies specifically targeting the vulnerable population in the Davao Region had been previously unexplored. This paper investigated the COVID-19 incidence in the Davao Region from 03 Mar 2020, the earliest recorded date of onset, to 31 Aug 2021 using geospatial tools. The variables were visualized through choropleth maps and graduated symbols, and subsequently examined through spatial autocorrelation and hotspot analysis. Hotspots across the region were observed to be in high-density areas. These areas pose greater risks of infection due to the presence of a high concentration of cases. However, high case fatality rates were found in far-flung municipalities where access to COVID-19 healthcare facilities is a dilemma. In the COVID-19 setting and future disease outbreaks similar to COVID-19, results from this study may provide insights to government offices and other related agencies to improve healthcare systems and programs such as providing and initiating tailor-fitted isolation and consultation mechanisms appropriate to the vulnerable population in a community. [ FROM AUTHOR] Copyright of Philippine Journal of Science is the property of Science & Technology Information Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
The Coronavirus disease 2019 (COVID-19) has exposed many systemic vulnerabilities in many countries' health system, disaster preparedness, and adequate response capabilities. With the early lack of data and information about the virus and the many differing local-specific factors contributing to its transmission, managing its spread had been challenging. The current work presents a modified Susceptible-Exposed-Infectious-Recovered compartmental model incorporating intervention protocols during different community quarantine periods. The COVID-19 reported cases before the vaccine rollout in Davao City, Philippines, are utilized to obtain baseline values for key epidemiologic model parameters. The probable secondary infections (i.e., time-varying reproduction number) among other epidemiological indicators were computed. Results show that the cases in Davao City were driven by the transmission rates, positivity proportion, latency period, and the number of severely symptomatic patients. This paper provides qualitative insights into the transmission dynamics of COVID-19 along with the government's implemented intervention protocols. Furthermore, this modeling framework could be used for decision support, policy making, and system development for the current and future pandemics.