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Selected Works of Elvira De Lara-Tuprio
Article
Understanding COVID-19 Dynamics and the Effects of Interventions in the Philippines: A Mathematical Modelling Study
Mathematics Faculty Publications
  • Jamie M Caldwell, University of Hawaii at Manoa
  • Elvira P De Lara-Tuprio, Ateneo de Manila University
  • Timothy Robin Y Teng, Ateneo de Manila University
  • Ma. Regina Justina E Estuar, Ateneo de Manila University
  • Raymond Francis R Sarmiento, National Institutes of Health, University of the Philippines, Manila
  • Milinda Abayawardana B Eng, Monash University
  • Robert Neil F Leong, University of New South Wales
  • Richard T Gray, University of New South Wales
  • James G Wood, University of New South Wales
  • Linh-Vi Le, World Health Organization Regional Office for the Western Pacific
  • Emma S McBryde, Australian Institute of Tropical Health and Medicine, James Cook University
  • Romain Ragonnet, Monash University
  • James M Trauer, Monash University
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Document Type
Article
Publication Date
7-14-2021
Disciplines
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.

Citation Information
Caldwell, J. M., Lara-Tuprio, E. de, Teng, T. R., Estuar, M. R. J. E., Sarmiento, R. F. R., Abayawardana, M., Leong, R. N. F., Gray, R. T., Wood, J. G., Le, L.-V., McBryde, E. S., Ragonnet, R., & Trauer, J. M. (2021). Understanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study. The Lancet Regional Health – Western Pacific, 14. https://doi.org/10.1016/j.lanwpc.2021.100211