Computational modeling to address the burden of influenza and strategies of control measures in Thailand

[摘要] Influenza is one of re-emerging infectious disease in Thailand. The true burden of influenza is not known and is needed for influenza preparedness. Thailand has a vaccine policy targets at healthcare worker (HCWs), people aged 6-24 months or ≥65 years, people with chronic medical condition (CMC), and pregnant women. However, amount of vaccine is limited and policy planners need information for vaccine prioritization. The government also promote non-pharmaceutical interventions, but their impact is not well studied. This research aimed to use agent-based model (ABM) to estimate influenza burden in Thailand and assess impact of control measures. The basic reproductive number (R0) based on Thailand's context is unknown and should be estimated for further studies of influenza dynamics. The R0 was estimated using formula relating the epidemic growth rate (r) and generation time. The projection of influenza burden was studied by fitting an ABM. The model contains a 58,354,744 synthetic Thai population, incorporates people with CMC and HCWs. At start, 100 agents were randomly assigned for initial infection. The model simulated the interactions of individuals with others over 180 days. Impacts of influenza vaccine were simulated at 50%, 75% and 100% coverage. Impacts of face mask wearing and hand washing were simulated at 10%, 25%, 50%, 75% and 100% coverage. The R0 estimates ranged from 1.11 to 1.77 (median 1.39). The highest attack rate occurs in school-age children and adolescents (15.32%). One Hundred percent coverage of target population policy can avoid morbidity and mortality by 47.06% and 59.61% in total population respectively. However, the benefit is very small for HCWs (3.75% case reduction). The extended policy to include children aged 2-18 years old can avoid >99% of cases. For non-pharmaceutical interventions, at least 50% compliance of the combined face mask use and hand washing policy can avoid morbidity and mortality >98% for all adherence of mask wearing. The public health significance of this research is that it provided information for health policy makers to guide optimized target population for vaccine, and to encourage non-pharmaceutical interventions for controlling influenza outbreak.

[发布机构] the University of Pittsburgh