Promoting healthy populations as a pandemic preparedness strategy: a simulation study from Mexico.

Background: The underlying health status of populations was a major determinant of the impact of the COVID-19 pandemic, particularly obesity prevalence. Mexico was one of the most severely affected countries during the COVID-19 pandemic and its obesity prevalence is among the highest in the world. It is unknown by how much the COVID-19 burden could have been reduced if systemic actions had been implemented to reduce excess weight in Mexico before the onset of the pandemic. Methods: Using a dynamic epidemic model based on nationwide data, we compare actual deaths with those under hypothetical scenarios assuming a lower body mass index in the Mexican population, as observed historically. We also model the number of deaths that would have been averted due to earlier implementation of front-of-pack warning labels or due to increases in taxes on sugar-sweetened beverages and non-essential high-energy foods in Mexico. Findings: We estimate that 52.5% (95% prediction interval (PI) 43.2, 61.6%) of COVID-19 deaths were attributable to obesity for adults aged 20-64 and 23.8% (95% PI 18.7, 29.1%) for those aged 65 and over. Had the population BMI distribution remained as it was in 2000, 2006, or 2012, COVID-19 deaths would have been reduced by an expected 20.6% (95% PI 16.9, 24.6%), 9.9% (95% PI 7.3, 12.9%), or 6.9% (95% PI 4.5, 9.5%), respectively. If the food-labelling intervention introduced in 2020 had been introduced in 2018, an expected 6.2% (95% PI 5.2, 7.3%) of COVID-19 deaths would have been averted. If taxes on sugar-sweetened beverages and high-energy foods had been doubled, trebled, or quadrupled in 2018, COVID-19 deaths would have been reduced by an expected 4.1% (95% PI 2.5, 5.7%), 7.9% (95% PI 4.9, 11.0%), or 11.6% (95% PI 7.3, 15.8%), respectively. Interpretation: Public health interventions targeting underlying population health, including non-communicable chronic diseases, is a promising line of action for pandemic preparedness that should be included in all pandemic plans. Funding: This study received funding from Bloomberg Philanthropies, awarded to Juan A. Rivera from the National Institute of Public Health; Community Jameel, the UK Medical Research Council (MRC), Kenneth C Griffin, and the World Health Organization.

The societal value of SARS-CoV-2 booster vaccination in Indonesia.

OBJECTIVES: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. METHODS: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million-dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. RESULTS: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. CONCLUSIONS: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

Data needs for integrated economic-epidemiological models of pandemic mitigation policies.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

Optimizing social and economic activity while containing SARS-CoV-2 transmission using DAEDALUS.

To study the trade-off between economic, social and health outcomes in the management of a pandemic, DAEDALUS integrates a dynamic epidemiological model of SARS-CoV-2 transmission with a multi-sector economic model, reflecting sectoral heterogeneity in transmission and complex supply chains. The model identifies mitigation strategies that optimize economic production while constraining infections so that hospital capacity is not exceeded but allowing essential services, including much of the education sector, to remain active. The model differentiates closures by economic sector, keeping those sectors open that contribute little to transmission but much to economic output and those that produce essential services as intermediate or final consumption products. In an illustrative application to 63 sectors in the United Kingdom, the model achieves an economic gain of between £161 billion (24%) and £193 billion (29%) compared to a blanket lockdown of non-essential activities over six months. Although it has been designed for SARS-CoV-2, DAEDALUS is sufficiently flexible to be applicable to pandemics with different epidemiological characteristics.

Healthy Life-Years Lost and Excess Bed-Days Due to 6 Patient Safety Incidents: Empirical Evidence From English Hospitals.

BACKGROUND: There is little satisfactory evidence on the harm of safety incidents to patients, in terms of lost potential health and life-years. OBJECTIVE: To estimate the healthy life-years (HLYs) lost due to 6 incidents in English hospitals between the years 2005/2006 and 2009/2010, to compare burden across incidents, and estimate excess bed-days. RESEARCH DESIGN: The study used cross-sectional analysis of the medical records of all inpatients treated in 273 English hospitals. Patients with 6 types of preventable incidents were identified. Total attributable loss of HLYs was estimated through propensity score matching by considering the hypothetical remaining length and quality of life had the incident not occurred. RESULTS: The 6 incidents resulted in an annual loss of 68 HLYs and 934 excess bed-days per 100,000 population. Preventable pressure ulcers caused the loss of 26 HLYs and 555 excess bed-days annually. Deaths in low-mortality procedures resulted in 25 lost life-years and 42 bed-days. Deep-vein thrombosis/pulmonary embolisms cost 12 HLYs, and 240 bed-days. Postoperative sepsis, hip fractures, and central-line infections cost <6 HLYs and 100 bed-days each. DISCUSSION: The burden caused by the 6 incidents is roughly comparable with the UK burden of Multiple Sclerosis (80 DALYs per 100,000), HIV/AIDS and Tuberculosis (63 DALYs), and Cervical Cancer (58 DALYs). There were marked differences in the harm caused by the incidents, despite the public attention all of them receive. Decision makers can use the results to prioritize resources into further research and effective interventions.