Suchergebnisse

Although large outbreaks of hepatitis E are regularly identified in south Asia, the majority of south Asian countries lack surveillance systems for this disease, which has hindered burden of disease estimates and prioritization of resources for prevention. Our study aimed to identify small hepatitis E outbreaks through a sentinel private laboratory in Dhaka, Bangladesh. We identified patients with detectable IgM antibody against hepatitis E virus. We defined a small outbreak as at least two laboratory-confirmed cases or ≥ 2 acute jaundice cases from the sentinel cases' family, neighborhood, or workplace. From November 2008 to November 2009, we identified 29 small outbreaks of hepatitis E from one private laboratory. The median number of cases in each outbreak was three. Cases were identified every month. Eighteen outbreaks occurred among families or neighbors, and 11 in the workplace. Among 103 cases identified as part of outbreaks, 31 (30%) sought care for diagnosis. In Bangladesh, collaboration between government public health surveillance and private laboratories can strengthen capacity for outbreak detection and improve estimates of disease burden.

Given the high morbidity and mortality among children in low- and middle-income countries as a result of preventable causes, the U.S. government and the United Nations Children's Fund convened an Evidence Summit on Enhancing Child Survival and Development in Lower- and Middle-Income Countries by Achieving Population-Level Behavior Change on June 3–4, 2013, in Washington, D.C. This article summarizes evidence for technological advances associated with population-level behavior changes necessary to advance child survival and healthy development in children under 5 years of age in low- and middle-income countries. After a rigorous evidence selection process, the authors assessed science, technology, and innovation papers that used mHealth, social/transmedia, multiplatform media, health literacy, and devices for behavior changes supporting child survival and development. Because of an insufficient number of studies on health literacy and devices that supported causal attribution of interventions to outcomes, the review focused on mHealth, social/transmedia, and multiplatform media. Overall, this review found that some mHealth interventions have sufficient evidence to make topic-specific recommendations for broader implementation, scaling, and next research steps (e.g., adherence to HIV/AIDS antiretroviral therapy, uptake and demand of maternal health service, and compliance with malaria treatment guidelines). While some media evidence demonstrates effectiveness in changing cognitive abilities, knowledge, and attitudes, evidence is minimal on behavioral endpoints linked to child survival. Population level behavior change is necessary to end preventable child deaths. Donors and low- and middle-income countries are encouraged to implement recommendations for informing practice, policy, and research decisions to fully maximize the impact potential of mHealth and multimedia for child survival and development.

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike.

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike. © 2020, The Author(s). ; https://doi.org/10.1038/s41597-020-00610-2

INTRODUCTION: SARS-CoV-2 has disproportionately affected disadvantaged communities across the USA. Risk perceptions for social interactions and essential activities during the COVID-19 pandemic may vary by sociodemographic factors. METHODS: We conducted a nationally representative online survey of 1592 adults in the USA to understand risk perceptions related to transmission of COVID-19 for social (eg, visiting friends) and essential activities (eg, medical visits or returning to work). We assessed relationships for activities using bivariate comparisons and multivariable logistic regression modelling, between responses of safe and unsafe, and participant characteristics. Data were collected and analysed in 2020. RESULTS: Among 1592 participants, risk perceptions of unsafe for 13 activities ranged from 29.2% to 73.5%. Large gatherings, indoor dining and visits with elderly relatives had the highest proportion of unsafe responses (>58%), while activities outdoor, accessing healthcare and going to the grocery store had the lowest (<36%). Older respondents were more likely to view social gatherings and indoor activities as unsafe but less likely for other activities, such as going to the grocery store and accessing healthcare. Compared with white/Caucasian respondents, black/African-American and Hispanic/Latino respondents were more likely to view activities such as dining and visiting friends outdoor as unsafe. Generally, men versus women, Republicans versus Democrats and independents, and individuals with higher versus lower income were more likely to view activities as safe. CONCLUSION: Evidence-based interventions should be tailored to sociodemographic differences in risk perception, access to information and health behaviours when implementing efforts to control the COVID-19 pandemic.