Assessing potential surge of COVID-19 cases and the need for booster vaccine amid emerging SARS-CoV-2 variants in Indonesia: A modelling study from West Java.

Objectives: Primary and booster vaccinations are crucial in COVID-19 control. This study aimed to assess the minimum booster coverage to hamper potential surge of COVID-19 cases in 2023 in Indonesia, a low-resource setting country. Methods: We used a modified SEIR compartment model to assess different scenarios in booster coverage across West Java population: 35%, 50%, and 70%. We fitted the model, then we calculated the potential active cases in 2023 if each scenario was met before 2022 ends. A heat map of predicted cases from various booster coverages and time frames was produced and matched with vaccination rate's function to determine feasible time frames. Results: A minimum of 70% booster coverage in West Java is needed to reduce 90% of potential COVID-19 cases and avert possible surge in 2023. The booster doses should be distributed before February 2023 to achieve its optimum preventive effect. Delays in achieving minimum booster coverage is acceptable, but higher booster coverage will be required. Conclusions: For better COVID-19 control in Indonesia, booster vaccination is warranted, as presented by a case study in West Java. Sufficient vaccine supplies, infrastructure, and healthcare workers should be ensured to support a successful booster vaccination program.

Infectious Disease Modeling with Socio-Viral Behavioral Aspects-Lessons Learned from the Spread of SARS-CoV-2 in a University.

When it comes to understanding the spread of COVID-19, recent studies have shown that pathogens can be transmitted in two ways: direct contact and airborne pathogens. While the former is strongly related to the distancing behavior of people in society, the latter are associated with the length of the period in which the airborne pathogens remain active. Considering those facts, we constructed a compartmental model with a time-dependent transmission rate that incorporates the two sources of infection. This paper provides an analytical and numerical study of the model that validates trivial insights related to disease spread in a responsive society. As a case study, we applied the model to the COVID-19 spread data from a university environment, namely, the Institut Teknologi Bandung, Indonesia, during its early reopening stage, with a constant number of students. The results show a significant fit between the rendered model and the recorded cases of infections. The extrapolated trajectories indicate the resurgence of cases as students' interaction distance approaches its natural level. The assessment of several strategies is undertaken in this study in order to assist with the school reopening process.