IntroductionThe onset of the SARS-CoV-2 pandemic alerted the Philippine government to impose the enhanced community quarantine (ECQ) as a means to hamper human mobility and interaction and eventually diminish transmission. Due to severe limitations in accessibility to basic needs due to ECQ, the government devised amelioration programs. A year after the declaration of the SARS-CoV-2 pandemic, variants of concern were detected locally. Consequently, there is a necessity to prepare reinstatement of strict non-pharmaceutical interventions while meeting the food-related basic needs of the population. Studies related to food distribution during a strict community quarantine have been lacking. The importance of allocating provisions during extreme pandemic measures should be properly analyzed, especially when attempts had been made by local government units.MethodsThis study devised an agent-based model (ABM) to observe the effects of the food relief system in mitigating the disease during Davao City ECQ when two variants are present in two adjacent villages. These relief distribution types are as follows: “regular and sufficient,” “regular but insufficient,” and “irregular” relief type. In total, three barangay scenarios were considered.Results and discussionFor the worst-case scenario, wherein a lot of infections are anticipated, the results show that the “irregular” relief type peaked at the highest number of cases, while the “regular and sufficient” relief type showed little to almost no new cases. The compromise-case scenario showed almost no difference between “regular but insufficient” and “regular and sufficient.” For the best-case scenario, the three relief types showed low average infected cases with almost small variance. The model was then compared, situationally, with Davao City barangays during ECQ and recommended which food relief type applies to the barangays. This could serve as a baseline on how food reliefs could be optimally distributed in cases where barangay conditions differently affect and transmit the SARS-CoV-2 virus of different variants with varying transmission rates within a community. Further development of the model should potentially be useful for decision support not only during pandemics but also in contexts where resource allocation to a community is involved.