Dataset Information

Modelling community-control strategies to protect hospital resources during an influenza pandemic in Ottawa, Canada.

ABSTRACT:

Background

A novel influenza virus has emerged to produce a global pandemic four times in the past one hundred years, resulting in millions of infections, hospitalizations and deaths. There is substantial uncertainty about when, where and how the next influenza pandemic will occur.

Methods

We developed a novel mathematical model to chart the evolution of an influenza pandemic. We estimate the likely burden of future influenza pandemics through health and economic endpoints. An important component of this is the adequacy of existing hospital-resource capacity. Using a simulated population reflective of Ottawa, Canada, we model the potential impact of a future influenza pandemic under different combinations of pharmaceutical and non-pharmaceutical interventions.

Results

There was substantial variation in projected pandemic impact and outcomes across intervention scenarios. In a population of 1.2 million, the illness attack rate ranged from 8.4% (all interventions) to 54.5% (no interventions); peak acute care hospital capacity ranged from 0.2% (all interventions) to 13.8% (no interventions); peak ICU capacity ranged from 1.1% (all interventions) to 90.2% (no interventions); and mortality ranged from 11 (all interventions) to 363 deaths (no interventions). Associated estimates of economic burden ranged from CAD $115 million to over $2 billion when extended mass school closure was implemented.

Discussion

Children accounted for a disproportionate number of pandemic infections, particularly in household settings. Pharmaceutical interventions effectively reduced peak and total pandemic burden without affecting timing, while non-pharmaceutical measures delayed and attenuated pandemic wave progression. The timely implementation of a layered intervention bundle appeared likely to protect hospital resource adequacy in Ottawa. The adaptable nature of this model provides value in informing pandemic preparedness policy planning in situations of uncertainty, as scenarios can be updated in real time as more data become available. However-given the inherent uncertainties of model assumptions-results should be interpreted with caution.

SUBMITTER: Saunders-Hastings P

PROVIDER: S-EPMC5470707 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Modelling community-control strategies to protect hospital resources during an influenza pandemic in Ottawa, Canada.

Saunders-Hastings Patrick P Quinn Hayes Bryson B Smith Robert R Krewski Daniel D

PloS one 20170614 6

<h4>Background</h4>A novel influenza virus has emerged to produce a global pandemic four times in the past one hundred years, resulting in millions of infections, hospitalizations and deaths. There is substantial uncertainty about when, where and how the next influenza pandemic will occur.<h4>Methods</h4>We developed a novel mathematical model to chart the evolution of an influenza pandemic. We estimate the likely burden of future influenza pandemics through health and economic endpoints. An imp ...[more]

PMID: 28614365

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Project description:IntroductionHuman influenza infection poses a serious public health threat in Cambodia, a country at risk for the emergence and spread of novel influenza viruses with pandemic potential. Prior pandemics demonstrated the adverse impact of influenza on poor communities in developing countries. Investigation of healthcare resource distribution can inform decisions regarding resource mobilization and investment for pandemic mitigation.MethodsA health facility survey performed across Cambodia obtained data on availability of healthcare resources important for pandemic influenza response. Focusing on five key resources considered most necessary for treating severe influenza (inpatient beds, doctors, nurses, oseltamivir, and ventilators), resource distributions were analyzed at the Operational District (OD) and Province levels, refining data analysis from earlier studies. Resources were stratified by respondent type (hospital vs. District Health Office [DHO]). A summary index of distribution inequality was calculated using the Gini coefficient. Indices for local spatial autocorrelation were measured at the OD level using geographical information system (GIS) analysis. Finally, a potential link between socioeconomic status and resource distribution was explored by mapping resource densities against poverty rates.ResultsGini coefficient calculation revealed variable inequality in distribution of the five key resources at the Province and OD levels. A greater percentage of the population resides in areas of relative under-supply (28.5%) than over-supply (21.3%). Areas with more resources per capita showed significant clustering in central Cambodia while areas with fewer resources clustered in the northern and western provinces. Hospital-based inpatient beds, doctors, and nurses were most heavily concentrated in areas of the country with the lowest poverty rates; however, beds and nurses in Non-Hospital Medical Facilities (NHMF) showed increasing concentrations at higher levels of poverty.ConclusionsThere is considerable heterogeneity in healthcare resource distribution across Cambodia. Distribution mapping at the local level can inform policy decisions on where to stockpile resources in advance of and for reallocation in the event of a pandemic. These findings will be useful in determining future health resource investment, both for pandemic preparedness and for general health system strengthening, and provide a foundation for future analyses of equity in health services provision for pandemic mitigation planning in Cambodia.

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.

Dataset Information

Modelling community-control strategies to protect hospital resources during an influenza pandemic in Ottawa, Canada.

Background

Methods

Results

Discussion

Publications

Modelling community-control strategies to protect hospital resources during an influenza pandemic in Ottawa, Canada.

Similar Datasets

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