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

Abstract

Background: COVID-19 initially caused less severe outbreaks in many low-and middle-income countries (LMIC) compared with many high-income countries, possibly because of differing demographics, socioeconomics, surveillance, and policy responses. Here, we investigate the role of multiple factors on COVID-19 dynamics in the Philippines, a LMIC that has had a relatively severe COVID-19 outbreak. Methods:We 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 first wave of 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 interventions.Findings: Population 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. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%, population recovered at ~9%, and scenario projections indicated high sensitivity to MHS adherence.Interpretation: COVID-19 dynamics in the Philippines are driven by age, contact structure, mobility, and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed, but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern.

COVID-19 vaccine brand hesitancy and other challenges to vaccination in the Philippines

“…To end this pandemic, it is critical to implement all possible public health interventions and strategies from face masks, physical distancing, to getting vaccinated [4,23]. However, there is a need to recognise that the adoption of all these interventions is influenced by individual risk perceptions, and these perceptions are shaped by various sources of information and experiences [24].…”

Parameter Estimation for a Modified SEIR Model of the COVID-19 Dynamics in the Philippines using Genetic Algorithm

“…Genetic algorithm is a heuristic search or optimization technique that belongs to a larger class of evolutionary algorithms and relies on randomness in crossover and mutation processes between the highest quality or "fittest" chromosomes. It employs the Darwinian concept of natural evolution which involves five (5) processes: an initial population, a fitness (or objective) function, selection, crossover, and mutation [12]. Through these processes, the genetic algorithm makes new generation of chromosomes by making randomized changes to certain genes in the chromosomes belonging to the prior generation.…”

“…The first COVID case in the Philippines was detected on 30 January 2020 and the National Capital Region was placed under the Enhanced Community Quarantine (ECQ) on 15 March 2020, which was extended to the entire Luzon island on 16 March 2020. Since then, several research groups based in the Philippines have attempted to predict the rise of cases using various methods [1], and the most common ones are the time-series analysis [2,3], compartmental models [4,5,6,7,8], and agent-based models [9,10,11].…”

Projections of the transmission of the Omicron variant for Toronto, Ontario, and Canada using surveillance data following recent changes in testing policies

“…The beneficial implementation of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-COV-2 has been widely studied ( Yuan et al, 2022 ; Ngonghala et al, 2020 ; Hellewell et al, 2020 ; Yuan et al, 2020 ), even in combination with vaccination ( McCoy et al, 2020 ; Layton & Sadria, 2022 ; Brüssow & Zuber, 2021 ; Tong et al, 2022 ; Aruffo et al, 2021 ). After almost three years of restrictions and implementation of NPIs, people's adherence to follow and respect the rules has been changing over time, and this had a great impact on the actual mechanisms of virus transmission ( Caldwell et al, 2021 ; Ejigu et al, 2021 ; Pedro et al, 2020 ; Lafzi et al, 2021 ). Social behaviour also depends on the perception of severity that individuals have due to the change in number of deaths or infections, leading to a change of the infections' transmission ( Weitz et al, 2020 ; Lin et al, 2020 ).…”