Rescinding community mitigation strategies in an influenza pandemic.
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ABSTRACT:
SUBMITTER: Davey VJ
PROVIDER: S-EPMC2570828 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
| S-EPMC1458676 | biostudies-literature
Project description:We used a hybrid transmission and economic model to evaluate the relative merits of stockpiling antiviral drugs and vaccine for pandemic influenza mitigation. In the absence of any intervention, our base-case assumptions generated a population clinical attack rate of 31.1%. For at least some parameter values, population prepandemic vaccination strategies were effective at containing an outbreak of pandemic influenza until the arrival of a matched vaccine. Because of the uncertain nature of many parameters, we used a probabilistic approach to determine the most cost-effective strategies. At a willingness to pay of >A$24,000 per life-year saved, more than half the simulations showed that a prepandemic vaccination program combined with antiviral treatment was cost-effective in Australia.
| S-EPMC2957998 | biostudies-literature
Project description:BackgroundThe threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories.MethodsAn economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%.ResultsFor a pandemic with basic reproduction number R0 = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death.ConclusionsFor pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.
| S-EPMC3606600 | biostudies-literature
Project description:We report the results of a national survey conducted to help public health officials understand the public's response to community mitigation interventions for a severe outbreak of pandemic influenza. Survey results suggest that if community mitigation measures are instituted, most respondents would comply with recommendations but would be challenged to do so if their income or job were severely compromised. The results also indicate that community mitigation measures could cause problems for persons with lower incomes and for racial and ethnic minorities. Twenty-four percent of respondents said that they would not have anyone available to take care of them if they became sick with pandemic influenza. Given these results, planning and public engagement will be needed to encourage the public to be prepared.
| S-EPMC2600239 | biostudies-literature
Project description:Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R(0) and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.
| S-EPMC3037387 | biostudies-literature
Project description:A significant feature of influenza pandemics is multiple waves of morbidity and mortality over a few months or years. The size of these successive waves depends on intervention strategies including antivirals and vaccination, as well as the effects of immunity gained from previous infection. However, the global vaccine manufacturing capacity is limited. Also, antiviral stockpiles are costly and thus, are limited to very few countries. The combined effect of antivirals and vaccination in successive waves of a pandemic has not been quantified. The effect of acquired immunity from vaccination and previous infection has also not been characterized. In times of a pandemic threat countries must consider the effects of a limited vaccine, limited antiviral use and the effects of prior immunity so as to adopt a pandemic strategy that will best aid the population. We developed a mathematical model describing the first and second waves of an influenza pandemic including drug therapy, vaccination and acquired immunity. The first wave model includes the use of antiviral drugs under different treatment profiles. In the second wave model the effects of antivirals, vaccination and immunity gained from the first wave are considered. The models are used to characterize the severity of infection in a population under different drug therapy and vaccination strategies, as well as school closure, so that public health policies regarding future influenza pandemics are better informed.
| S-EPMC3004963 | biostudies-literature
Project description:BACKGROUND: The 2009 influenza A (H1N1) pandemic has required decision-makers to act in the face of substantial uncertainties. Simulation models can be used to project the effectiveness of mitigation strategies, but the choice of the best scenario may change depending on model assumptions and uncertainties. METHODS: We developed a simulation model of a pandemic (H1N1) 2009 outbreak in a structured population using demographic data from a medium-sized city in Ontario and epidemiologic influenza pandemic data. We projected the attack rate under different combinations of vaccination, school closure and antiviral drug strategies (with corresponding "trigger" conditions). To assess the impact of epidemiologic and program uncertainty, we used "combinatorial uncertainty analysis." This permitted us to identify the general features of public health response programs that resulted in the lowest attack rates. RESULTS: Delays in vaccination of 30 days or more reduced the effectiveness of vaccination in lowering the attack rate. However, pre-existing immunity in 15% or more of the population kept the attack rates low, even if the whole population was not vaccinated or vaccination was delayed. School closure was effective in reducing the attack rate, especially if applied early in the outbreak, but this is not necessary if vaccine is available early or if pre-existing immunity is strong. INTERPRETATION: Early action, especially rapid vaccine deployment, is disproportionately effective in reducing the attack rate. This finding is particularly important given the early appearance of pandemic (H1N1) 2009 in many schools in September 2009.
| S-EPMC2774362 | biostudies-literature
Project description:To project the potential economic impact of pandemic influenza mitigation strategies from a societal perspective in the United States.We use a stochastic agent-based model to simulate pandemic influenza in the community. We compare 17 strategies: targeted antiviral prophylaxis (TAP) alone and in combination with school closure as well as prevaccination.In the absence of intervention, we predict a 50% attack rate with an economic impact of $187 per capita as loss to society. Full TAP (FTAP) is the most effective single strategy, reducing number of cases by 54% at the lowest cost to society ($127 per capita). Prevaccination reduces number of cases by 48% and is the second least costly alternative ($140 per capita). Adding school closure to FTAP or prevaccination further improves health outcomes but increases total cost to society by approximately $2700 per capita.FTAP is an effective and cost-saving measure for mitigating pandemic influenza.
| S-EPMC3710126 | biostudies-literature
Project description:BackgroundThe US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience?Methods and findingsWe systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience.ConclusionsSystematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic.
| S-EPMC2432023 | biostudies-literature
Project description:IntroductionCommunity mitigation strategies (CMS) have demonstrated to be effective in the reduction of transmission and incidence of COVID-19, especially in the population with symptoms associated with the disease. The aim of this study was to evaluate the association between the presence of COVID-19 symptoms and adherence to CMS in Latin American adults.MethodsWe carried out a secondary analysis of a database developed by the University of Maryland and Facebook social network during the COVID-19 pandemic. We included Latin American adults that used the Facebook platform and participated in a survey conducted from April 23 to May 23, 2020. The principal outcome variable was reported compliance with the three main CMS (physical distancing, use of face masks, and hand washing). The exposure variable included symptoms suspicious for COVID-19 defined as the presence of three or more symptoms of an acute clinical case of COVID-19. We performed generalized linear models of the Poisson family with a logarithmic link function to evaluate the association between the presence of COVID-19 symptoms and reported compliance with CMS. We calculated crude and adjusted prevalence ratios (PR) with their 95% confidence intervals (95%CI).ResultsWe analyzed 1,310,690 adults from Latin America; 48.1% were male and 42.9% were under 35 years of age. The prevalence of suspicious symptoms of COVID-19 was 18.5% and reported compliance with the three CMS was 45.3%. The countries with the highest proportion of reported compliance with the three CMS were Peru, Bolivia and Panama, while those with the lowest reported compliance were Costa Rica, Nicaragua and Honduras. In the adjusted model, people with suspicious symptoms for COVID-19 had a 14% lower compliance with the three CMS (aPR = 0.86; 95%CI: 0.85-0.87; p < 0.001).ConclusionsLess than half of the participants complied with the CMS, and those presenting suspicious symptoms for COVID-19 had lower reported compliance with the three CMS.
| S-EPMC8662838 | biostudies-literature