Modeling behavior change and underreporting in the early phase of COVID-19 pandemic in Metro Manila, Philippines

ABSTRACT

IntroductionAt the start of the pandemic, the Philippine capital Metro Manila was placed under a strict lockdown termed Enhanced Community Quarantine (ECQ). When ECQ was eased to General Community Quarantine (GCQ) after three months, healthcare systems were soon faced with a surge of COVID-19 cases, putting most facilities at high or critical risk and prompting a return to a stricter policy. MethodsWe developed a mathematical model considering behavior changes and underreporting to represent the first major epidemic wave in Metro Manila. Key parameters were fitted to the cumulative cases in the capital from March to September 2020. A bi-objective optimization problem was formulated that allows easing of restrictions at an earlier time and minimizes the necessary additional beds to ensure sufficient capacity in healthcare facilities once ECQ was lifted. ResultsIf behavior was changed one to four weeks earlier before GCQ, then the cumulative number of cases can be reduced by up to 55% and the peak delayed by up to four weeks. Increasing the reporting ratio during ECQ threefold may increase the reported cases by 23% but can reduce the total cases, including the unreported, by 61% on June 2020. If GCQ began on May 28, 2020, 48 beds should have been added per day to keep the capacity only at high-risk (75% occupancy). Among the optimal solutions, the peak of cases is lowest if ECQ was lifted on May 20, 2020 and with at least 56 additional beds per day. ConclusionSince infectious diseases are likely to reemerge, the formulated model can be used as a decision support tool to improve existing policies and plan effective strategies that can minimize the socioeconomic impact of strict lockdown measures and ensure adequate healthcare capacity.