Sustaining effective COVID-19 control in Malaysia through large-scale vaccination (preprint)

Introduction As of 3rd June 2021, Malaysia is experiencing a resurgence of COVID-19 cases. In response, the federal government has implemented various non-pharmaceutical interventions (NPIs) under a series of Movement Control Orders and, more recently, a vaccination campaign to regain epidemic control. In this study, we assessed the potential for the vaccination campaign to control the epidemic in Malaysia and four high-burden regions of interest, under various public health response scenarios. Methods A modified susceptible-exposed-infectious-recovered compartmental model was developed that included two sequential incubation and infectious periods, with stratification by clinical state. The model was further stratified by age and incorporated population mobility to capture NPIs and micro-distancing (behaviour changes not captured through population mobility). Emerging variants of concern (VoC) were included as an additional strain competing with the existing wild-type strain. Several scenarios that included different vaccination strategies (i.e. vaccines that reduce disease severity and/or prevent infection, vaccination coverage) and mobility restrictions were implemented. Results The national model and the regional models all fit well to notification data but underestimated ICU occupancy and deaths in recent weeks, which may be attributable to increased severity of VoC or saturation of case detection. However, the true case detection proportion showed wide credible intervals, highlighting incomplete understanding of the true epidemic size. The scenario projections suggested that under current vaccination rates complete relaxation of all NPIs would trigger a major epidemic. The results emphasise the importance of micro-distancing, maintaining mobility restrictions during vaccination roll-out and accelerating the pace of vaccination for future control. Malaysia is particularly susceptible to a major COVID-19 resurgence resulting from its limited population immunity due to the historical success of the country in maintaining control throughout much of 2020.

Understanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study (preprint)

BackgroundCOVID-19 appears to have caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with high-income countries, possibly because of differing demographics, socio-economics, climate, surveillance, and policy responses. The Philippines is a LMIC that has had a relatively severe COVID-19 outbreak but has recently curtailed transmission while gradually easing interventions. MethodsWe applied an age-structured compartmental model that incorporated time-varying mobility, testing, and personal protective behaviors (through a "Minimum Health Standards" policy, MHS) to represent the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon, Central Visayas, and the National Capital Region). We estimated effects of control measures, key epidemiological parameters, and projected the impacts of easing interventions. ResultsPopulation age structure, contact rates, mobility, testing, and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases, hospitalisations, and deaths. Several of the fitted epidemiological parameters were consistent with those reported in high-income settings. The model indicated that MHS reduced the probability of transmission per contact by 15-32%. The December 2020 case detection rate was estimated at [~]14%, population recovered at [~]12%, and scenario projections indicated high sensitivity to MHS adherence. ConclusionsCOVID-19 dynamics in the Philippines are driven by age, contact structure, and mobility, and the epidemic can be understood within a similar framework as for high-income settings. Continued compliance with low-cost MHS measures should allow the Philippines to maintain epidemic control, but disease resurgence remains a threat due to low population immunity and detection rates.

Age-targeted dose allocation can halve COVID-19 vaccine requirements (preprint)

In anticipation of COVID-19 vaccine deployment, we use an age-structured mathematical model to investigate the benefits of optimizing age-specific dose allocation to suppress SARS-CoV-2 transmission. Across 179 countries, we find that the highest priority individuals are typically those between 30 and 59 years of age because of their high contact rates and higher risk of infection and disease. We reaffirm that vaccination alone may be insufficient to achieve herd immunity in some settings, and that additional intervention measures may be required. Nevertheless, we show that optimizing the allocation of vaccine doses can more than double their effectiveness.