Guidelines
UNAIDS/WHO working group on global HIV/AIDS and STI surveillance
August 2015
HIV strategic information for impact
Circulating vaccine-derived poliovirus type 2 in Angola
Ebola virus disease in Democratic Republic of the Congo
Dengue fever in Côte d’Ivoire
Humanitarian crisis in north-east Nigeria.
HIV Prevalence: Data from the 2010 Rwanda Demographic and Health Survey.
This document is to support local authorities, leaders and policy-makers in cities and other urban settlements in identifying effective approaches and implementing recommended actions that enhance the prevention, preparedness and readiness for COVID-19 in urban settings, to ensure a robust response ...and eventual recovery. It covers factors unique to cities and urban settings, considerations in urban preparedness, key areas of focus and preparing for future emergencies.
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Special Focus on COVID-19
The report provides updated estimates for drinking water, sanitation and hygiene in schools including progress from 2015 to 2019. It highlights the rapid improvement needed to ensure students have access to handwashing facilities with soap and water during the COVID-19 pan...demic, and to meet associated SDG targets by 2030.
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Six months in, the indirect impacts of COVID-19 take a toll on health, social and economic outcomes.
The WHO Regional Office for Europe has established the Childhood Obesity Surveillance Initiative in more than half thecountries in the Region for routine monitoring of the policy response to the emerging obesity epidemic. The aim of the system is to measure trends in overweight and obesity in childr...en aged 6.0–9.9 years for accurate understanding of the epidemic and to allow inter-country comparisons. This document outlines the data collection procedures agreed for use in the Initiative.
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12 May 2021. This third survey in the series shows that the COVID-19 pandemic continues to impact societies, not only in terms of health, but also social and economic conditions and day-to-day life
This report is part of the gender and noncommunicable diseases (NCDs) initiative launched by the WHO Regional Office for Europe, which aims to strengthen the response to NCDs through a gender approach. It is part of a series of country profiles and a synthesis report. The country profile of Ukraine ...presents a gender analysis of the WHO STEPwise survey (STEPS) data to support international commitments to reducing the burden of NCDs with evidence and knowledge exchange. A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and accessing services by sociodemographic variables. Important differences hide even in sex-disaggregated data that need to be unpacked through sociodemographic characteristics, because men and women are not homogenous groups. The report also recognizes gaps in evidence and calls for further analysis of the impact of gender-based inequalities.
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Sustainable transport systems can protect and promote health, by reducing risks from vehicular air pollution, physical inactivity and traffic injuries, and by providing climate and environmental benefits for urban areas.
World Humanitarian Data and Trends presents global- and country-level data-and-trend analysis about humanitarian
crises and assistance. Its purpose is to consolidate this information and present it in an accessible way, providing policymakers, researchers and humanitarian practitioners with an evid...ence base to support humanitarian policy decisions and provide context for operational decisions.
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Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status—wealth and education—differ among... high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management.
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