for their valuable technical and editorial contributions to the chapter.
IntroductionRobust metrics for national-level preparedness are critical for assessing global resilience to epidemic and pandemic outbreaks. However, existing preparedness assessments focus primarily on public health systems or specific legislative frameworks, and do not measure other essential capacities that enable and support public health preparedness and response.MethodsWe developed an Epidemic Preparedness Index (EPI) to assess national-level preparedness. The EPI is global, covering 188 countries. It consists of five subindices measuring each country’s economic resources, public health communications, infrastructure, public health systems and institutional capacity. To evaluate the construct validity of the EPI, we tested its correlation with proxy measures for preparedness and response capacity, including the timeliness of outbreak detection and reporting, as well as vaccination rates during the 2009 H1N1 influenza pandemic.ResultsThe most prepared countries were concentrated in Europe and North America, while the least prepared countries clustered in Central and West Africa and Southeast Asia. Better prepared countries were found to report infectious disease outbreaks more quickly and to have vaccinated a larger proportion of their population during the 2009 pandemic.ConclusionThe EPI measures a country’s capacity to detect and respond to infectious disease events. Existing tools, such as the Joint External Evaluation (JEE), have been designed to measure preparedness within a country over time. The EPI complements the JEE by providing a holistic view of preparedness and is constructed to support comparative risk assessment between countries. The index can be updated rapidly to generate global estimates of pandemic preparedness that can inform strategy and resource allocation.
The World Bank is publishing nine volumes of Disease Control Priorities, 3rd edition (DCP3) between 2015 and 2018. Volume 9, Improving Health and Reducing Poverty, summarises the main messages from all the volumes and contains cross-cutting analyses. This Review draws on all nine volumes to convey conclusions. The analysis in DCP3 is built around 21 essential packages that were developed in the nine volumes. Each essential package addresses the concerns of a major professional community (eg, child health or surgery) and contains a mix of intersectoral policies and health-sector interventions. 71 intersectoral prevention policies were identified in total, 29 of which are priorities for early introduction. Interventions within the health sector were grouped onto five platforms (population based, community level, health centre, first-level hospital, and referral hospital). DCP3 defines a model concept of essential universal health coverage (EUHC) with 218 interventions that provides a starting point for country-specific analysis of priorities. Assuming steady-state implementation by 2030, EUHC in lower-middle-income countries would reduce premature deaths by an estimated 4·2 million per year. Estimated total costs prove substantial: about 9·1% of (current) gross national income (GNI) in low-income countries and 5·2% of GNI in lower-middle-income countries. Financing provision of continuing intervention against chronic conditions accounts for about half of estimated incremental costs. For lower-middle-income countries, the mortality reduction from implementing the EUHC can only reach about half the mortality reduction in non-communicable diseases called for by the Sustainable Development Goals. Full achievement will require increased investment or sustained intersectoral action, and actions by finance ministries to tax smoking and polluting emissions and to reduce or eliminate (often large) subsidies on fossil fuels appear of central importance. DCP3 is intended to be a model starting point for analyses at the country level, but country-specific cost structures, epidemiological needs, and national priorities will generally lead to definitions of EUHC that differ from country to country and from the model in this Review. DCP3 is particularly relevant as achievement of EUHC relies increasingly on greater domestic finance, with global developmental assistance in health focusing more on global public goods. In addition to assessing effects on mortality, DCP3 looked at outcomes of EUHC not encompassed by the disability-adjusted life-year metric and related cost-effectiveness analyses. The other objectives included financial protection (potentially better provided upstream by keeping people out of the hospital rather than downstream by paying their hospital bills for them), stillbirths averted, palliative care, contraception, and child physical and intellectual growth. The first 1000 days after conception are highly important for child development, but the next 7000 days are likewise important and often neglected.
American hantaviruses cause a severe respiratory disease known as hantavirus pulmonary syndrome (HPS). In the United States, Sin Nombre virus (SNV), carried by the deer mouse ( Peromyscus maniculatus), is the etiologic agent in the majority of HPS cases. The relationship between deer mouse population density and SNV infection prevalence in deer mice is poorly understood. Our purpose was to clarify this relationship by demonstrating the existence of delayed-density-dependent prevalence of SNV infection in populations of wild deer mice. We also explored the relationship between SNV infection in deer mouse populations and the incidence of human HPS. The study population was 3,616 deer mice captured on 10 mark-recapture grids in Montana during May and September, 1994-2004. Using multivariate logistic regression analysis, we found a strong association between deer mouse population density in fall (September) and SNV antibody prevalence in deer mice the following spring (May). Other characteristics associated with SNV infection in deer mice in spring were: (1) presence of at least one infected deer mouse in the population the previous fall, (2) male gender, (3) adult age class, (4) presence of scars, (5) grassland and logged habitats, and (6) elevations below 1,300 m. There was a strong association between concurrently measured SNV antibody prevalence in deer mice and probable exposure of human HPS cases during the same time period. Human cases were more likely to occur during seasons when SNV antibody prevalence was at least 10% in deer mouse populations. These findings suggest that fall rodent population parameters could be used to help guide prevention efforts the following spring.
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