Economic Evaluation of Individual School Closure Strategies: The Hong Kong 2009 H1N1 Pandemic

Abstract

Background: School closures as a means of containing the spread of disease have received considerable attention from the public health community. Although they have been implemented during previous pandemics, the epidemiological and economic effects of the closure of individual schools remain unclear.

Methodology: This study used data from the 2009 H1N1 pandemic in Hong Kong to develop a simulation model of an influenza pandemic with a localised population structure to provide scientific justifications for and economic evaluations of individual-level school closure strategies.

Findings: The estimated cost of the study's baseline scenario was USD330 million. We found that the individual school closure strategies that involved all types of schools and those that used a lower threshold to trigger school closures had the best performance. The best scenario resulted in an 80% decrease in the number of cases (i.e., prevention of about 830,000 cases), and the cost per case prevented by this intervention was USD1,145; thus, the total cost was USD1.28 billion.

Conclusion: This study predicts the effects of individual school closure strategies on the 2009 H1N1 pandemic in Hong Kong. Further research could determine optimal strategies that combine various system-wide and district-wide school closures with individual school triggers across types of schools. The effects of different closure triggers at different phases of a pandemic should also be examined.

Fig 1. Closing schools based on the number of confirmed cases at a particular school (individual school closure)–Kindergarten.

Fig 2. Closing schools based on the number of confirmed cases at a particular school (individual school closure)–Kindergarten and Primary.

Fig 3. Closing schools based on the number of confirmed cases at a particular school (individual school closure)–All Schools.

Fig 4. Epidemic peaks of baseline and selected school closure scenarios (closure length: one week).

Fig 5. Cost-effectiveness of school closure strategies.

Note: Except for the baseline scenario, the other 8 school closure scenarios were run under 3 different school closure modes (K, KP, KPS) and 8 school closure periods (SCL 1, 2, 3, 4, 6, 8, 12, 16). Thus, there are 193 sets of experiments in total, each of which was comprised of 20 replications. The mean cost incurred and the overall attack rate under each set of experiments are displayed.

Fig 6. Sensitivity analyses with varying ascertainment rates.

Note: Except for the six baseline scenarios, the other 24 school closure scenarios (closure mode: KPS) were run under eight different school closure periods (SCL 1, 2, 3, 4, 6, 8, 12, 16). Thus, there are 198 sets of experiments in total, each of which was comprised of 20 replications. The mean cost incurred and the overall attack rate under each set of experiments are displayed.

Fig 7. Sensitivity analyses with varying conditional probabilities of withdrawal.

Note: Except for the two baseline scenarios, the other eight school closure scenarios (closure mode: KPS) were run under eight school closure periods (SCL 1, 2, 3, 4, 6, 8, 12, 16). Thus, there are 66 sets of experiments in total, each of which was comprised of 20 replications. The mean cost incurred and the overall attack rate under each set of experiments are displayed.

Fig 8. Cost-effectiveness in terms of overall attack rates (ARs) and cost (in billions of HKD).

Fig 9. Incremental cost-effectiveness ratios of the best scenarios.