Age-prioritized use of antivirals during an influenza pandemic

Abstract

Background: The WHO suggested that governments stockpile, as part of preparations for the next influenza pandemic, sufficient influenza antiviral drugs to treat approximately 25% of their populations. Our aim is two-fold: first, since in many countries the antiviral stockpile is well below this level, we search for suboptimal strategies based on treatment provided only to an age-dependent fraction of cases. Second, since in some countries the stockpile exceeds the suggested minimum level, we search for optimal strategies for post-exposure prophylactic treatment of close contacts of cases.

Methods: We used a stochastic, spatially structured individual-based model, considering explicit transmission in households, schools and workplaces, to simulate the spatiotemporal spread of an influenza pandemic in Italy and to evaluate the efficacy of interventions based on age-prioritized use of antivirals.

Results: Our results show that the antiviral stockpile required for treatment of cases ranges from 10% to 35% of the population for R0 in 1.4 - 3. No suboptimal strategies, based on treatment provided to an age-dependent fraction of cases, were found able to remarkably reduce both clinical attack rate and antiviral drugs needs, though they can contribute to largely reduce the excess mortality. Treatment of all cases coupled with prophylaxis provided to younger individuals is the only intervention resulting in a significant reduction of the clinical attack rate and requiring a relatively small stockpile of antivirals.

Conclusion: Our results strongly suggest that governments stockpile sufficient influenza antiviral drugs to treat approximately 25% of their populations, under the assumption that R0 is not much larger than 2. In countries where the number of antiviral stockpiled exceeds the suggested minimum level, providing prophylaxis to younger individuals is an option that could be taken into account in preparedness plans. In countries where the number of antivirals stockpiled is well below 25% of the population, priority should be decided based on age-specific case fatality rates. However, late detection of cases (administration of antivirals 48 hours after the clinical onset of symptoms) dramatically affects the efficacy of both treatment and prophylaxis.

Figure 1

Sociodemography. a Frequency distributions of household size for the different household types (in blue) and frequency distribution of the different household types (in red) considered in the model. b Age distribution from census data (blue) and simulated (red). c Proportion of workers for class of workplace from industry census data (blue) and simulated (red). d Probability density function of travel distances as obtained by using the gravity model (3) (in blue) compared with that obtained by using the the distance kernel (2) (in red).

Figure 2

Baseline simulations. Timing for initial case for R₀ = 1.4 (green), R₀ = 1.7 (blue), R₀ = 2 (red) and R₀ = 3 (violet) in the baseline scenarios. Histograms are based on 100 simulations each. b Expected case incidence over time (solid lines) and 95% confidence intervals (shaded regions) based on 100 simulations for each scenario. Colors as in a. The black time window indicate a reasonable time interval for the availability of a pandemic vaccine. c Cumulative clinical attack rate by age (colors as in a), compared with data on the 1918–19 pandemic [23] (black line). The vertical dashed lines identify the age classes, namely young, adults and elderly, defined for age-prioritization of the use of antivirals. d Expected excess mortality by age classes (colors as in a) as obtained by assuming two different age-specific case fatality rates, similar to those estimated for the 1918–19 pandemic in Copenhagen (solid lines) and for the 1969–70 pandemic in Italy (dashed lines). Note that in the latter case, the expected excess mortality in the younger age classes (0–64 years old) is very close to 0 for all the R₀ values considered.

Figure 3

Age-prioritized use of antivirals during an influenza pandemic in Italy: timing and impact. Clinical attack rates, peak day and peak daily clinical attack rate for baseline simulations (green), for antiviral treatment provided to index cases of all age classes (blue) or provided only to specific age classes (cyan, Y = young, A = adults, E = elderly), and for post-exposure prophylactic treatment provided to all age classes (red) or only to specific age classes (orange, Y = young, A = adults, E = elderly). When post-exposure prophylactic treatment is considered, we assume that antiviral treatment is also provided to index cases.

Figure 4

Age-prioritized use of antivirals during an influenza pandemic in Italy: excess mortality. Expected excess mortality as obtained by assuming two different age-specific case fatality rates, similar to those estimated for the 1918–19 influenza pandemic in Copenhagen and for the 1969–70 influenza pandemic in Italy respectively, for baseline simulations (green), for antiviral treatment provided to index cases of all age classes (blue) or provided only to specific age classes (cyan, Y = young, A = adults, E = elderly), and for post-exposure prophylactic treatment provided to all age classes (red) or only to specific age classes (orange, Y = young, A = adults, E = elderly).

Figure 5

Age-prioritized use of antivirals during an influenza pandemic in Italy: antiviral stockpile. Antiviral stockpile required and number of avoided cases divided by the number of persons treated for antiviral treatment provided to index cases of all age classes (blue) or provided only to specific age classes (cyan, Y = young, A = adults, E = elderly), and for post-exposure prophylactic treatment provided to all age classes (red) or only to specific age classes (orange, Y = young, A = adults, E = elderly). When post-exposure prophylactic treatment is considered, we assume that antiviral treatment is also provided to index cases. The horizontal black line represents the Italian antiviral stockpile.