Assessment Report of Surveillance System and Outbreak Investigation in Yello Health Center, Loma District: Case Study

Surveillance is used for the application of health information for action under the following general set of conditions: in case of emergency situation, when timely response is demanded, needs public health epidemiologist must travel to & work in the field to solve the problem and when the extent of investigation is likely to be limited because of the imperative for timely intervention.The WHO-AFRO IDSR strategy focuses on the district level, but the goal of the IDSR strategy is to develop sufficient surveillance and response capacities at each level of the national system so that a flexible national infectious disease surveillance system will result. In a national adaptation of the strategy, a country might choose to focus initially on a few diseases depending on national resources and capacities.This study was done to assess the public health surveillance system and outbreak investigation in selected Yello Health Center, Loma District, South Ethiopia by using a cross sectional study was conducted from January 14-25 2/ 2012 in Yello Health Center.The data from different case team units in the health center is compiled but not analyzed by person, place and time dimensions. They perform trend analysis for malaria case only. They are using the information from statistics office to get denominator populationsSupervisors from woreda health office came to the health center three times in the past six months. The health center had made once supervision per month on the facilities under the health office i.e. health posts but no document was found about the supervision at all health posts.The health center has received written feedback from woreda health office but not from regional and supervisors. There is no standard case management protocol and contingency plan for epidemic prone diseases and possible outbreak in the health center. Activities conducted by health center on communicable disease prevention and control during the past 3 month includes Vitamin A supplementation, health education, malaria case management, ITN distribution and mass campaign like DDT spray. There is epidemic committee at the health center level. They are contributing to epidemic response activities by conducting case management, providing health education and immunization activities.Based on the assessment made, there is slightly alive surveillance system in the health center.The activities of IDSR system in health center are poor as it is evidenced by poor recording, analyzing, reporting, supervision and feedback. Therefore, a health center should create a link between laboratory and epidemiologic surveillance and need to increase the capacity to confirm cases and report to next higher level and reporting pattern of priority diseases need to be frequent and in line with the guideline. This works similarly for reporting to higher level and feedback to health posts. Keywords: IDSR, outbreak, Yello, catchment area, Loma Distric

Rabies Prevalence, Prevention and Clinical Features in Case of Developing Countries: Article Review

Rabies is a viral disease that affects the central nervous system (CNS) of mammals and has an extremely high case fatality rate. It is widely distributed across the world, with only a few countries (mainly islands and peninsulas) that are free of the disease. It is a neglected disease of poor and vulnerable communities. Underreporting and not recording of cases made it unable to control.Africa and especially South East Asia and are the most common regions to be highly victims of dog bite rabies each year. Mostly young aged and rurals were commonly affected. All mammals are vulnerable to rabies, but only a limited number of species also act as reservoir hosts. They include members of the families Canidae (dogs, jackals, coyotes, wolves, foxes and raccoon dogs), Mustelidae (e.g., skunks), Viverridae (e.g., mongooses), and Procyonidae (raccoons), and the order Chiroptera (bats). Once clinical signs develop, there are very few survivors. Vaccines can protect pets, as well as people exposed to these animals, but the maintenance of rabies viruses in wildlife complicates control. In humans, illness can be prevented by administering anti-rabies antibodies and a series of vaccinations before the symptoms appear. However, people in impoverished countries do not always have access to effective post-exposure prophylaxis.In general, Domestic dogs serve as a major reservoir of rabies virus in many developing countries and are capable of maintaining virus transmission in a well-defined maintenance cycle. Cats are not known to act as maintenance reservoirs for unique rabies virus variants. They are important as incidental hosts affected by spillover and can serve as important in a chain of transmission of rabies virus to humans and other domestic animals. The only means to prevent rabies is ant rabies vaccination. Keywords: Domestic animals, Dogs, Developing Countries, Epidemiology, Human rabies, Vaccine Prevention and Contro

Health Care Seeking Behavior in Southwest Ethiopia

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Rural and urban populations have disparate socio-demographic and economic characteristics, which have an influence on equity and their health seeking behavior. We examined and compared the health care seeking behavior for perceived morbidity between urban and rural households in Southwest Ethiopia. Methods Analytic cross-sectional study was conducted among urban and rural households living in Esera district of Southwest Ethiopia. A random sample of 388 head of households (126 urban and 262 rural) were selected. A pretested and structured questionnaire was used for data collection with face-to-face interview. In addition to descriptive methods, binary logistic regression was used to identify factors associated with health seeking behavior at p value of less than 0.05. Results Of the sample household heads, 377 (97.2%) (119 urban and 258 rural) were successfully interviewed. Among these, 58.4% (95% CI, 53.3–63.3%) of the households sought care from modern health care that was lower among rural (48.1%) than urban (80.7%) households. The prevalence of self-treatment was 35.3% in urban and 46.1% in rural households. Among the factors considered for modern health care utilization, higher monthly income (AOR, 5.6; 95% CI, 2.04–15.4), perceived severity of disease (AOR, 2.5; 95% CI, 1.1–5.8), acute duration of disease (AOR, 8.9; 95% CI, 2.4–33.3) and short distance from health facilities (AOR, 3; 95% CI, 1.2–8.4) among rural and being married (AOR, 11.3; 95% CI, 1.2–110.2) and perceived severity of disease (AOR, 6.6; 95% CI, 1.1–10.9) among urban households showed statistically significant association. Conclusions The general health seeking behavior of households on perceived morbidity was satisfactory but lower in rural compared to urban households. Self-medication was also widely practiced in the study area. The findings signal the need to work more on accessibility and promotion of healthcare seeking behavior especially among rural households

The Effect of the COVID-19 Pandemic on the Social Inequalities of Health Care Use in Hungary: A Nationally Representative Cross-Sectional Study

Background: The social representation of restricted health care use during the COVID-19 pandemic has not been evaluated properly yet in Hungary. Objective: Our study aimed to quantify the effect of COVID-19 pandemic measures on general practitioner (GP) visits, specialist care, hospitalization, and cost-related prescription nonredemption (CRPNR) among adults, and to identify the social strata susceptible to the pandemic effect. Methods: This cross-sectional study was based on nationally representative data of 6611 (Nprepandemic = 5603 and Npandemic = 1008) adults. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing health care use by odds ratios (ORs) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to the pandemic effect, the interaction of the time of data collection with the level of education, marital status, and Roma ethnicity, was tested and described by iORs. Results: While the CRPNR did not change, the frequency of GP visits, specialist care, and hospitalization rates was remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic. Roma proved to be not specifically affected by the pandemic in any studied aspect, and the pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (iORGP visits, high-school vs. primary-education = 0.434; 95% CI 0.243-0.776, ORspecialist visit, high-school vs. primary-education = 0.598; 95% CI 0.364-0.985), and stronger among married adults (iORGP visit, widowed vs. married = 2.284; 95% CI 1.043-4.998, iORspecialist visit, widowed vs. married = 1.915; 95% CI 1.157-3.168), on the frequency of GP visits and specialist visits. The prepandemic CRPNR inequality by the level of education was increased (iORhigh-school vs. primary-education = 0.236; 95% CI 0.075–0.743). Conclusion: Primary educated and widowed adults did not follow the general trend, and their prepandemic health care use was not reduced during the pandemic. This shows that although the management of pandemic health care use restrictions was implemented by not increasing social inequity, the drug availability for primary educated individuals could require more support

Health Care Seeking Behavior in Southwest Ethiopia

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Male Partners Involvement in Prevention of Mother-to-Child Transmission of HIV Services in Southern Central Ethiopia: In Case of Lemo District, Hadiya Zone

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Self-Medication Practice in Limmu Genet, Jimma Zone, Southwest Ethiopia: Does Community Based Health Insurance Scheme Have an Influence?

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Global, regional, and national burden of tuberculosis, 1990–2016: results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 Study

Background Although a preventable and treatable disease, tuberculosis causes more than a million deaths each year. As countries work towards achieving the Sustainable Development Goal (SDG) target to end the tuberculosis epidemic by 2030, robust assessments of the levels and trends of the burden of tuberculosis are crucial to inform policy and programme decision making. We assessed the levels and trends in the fatal and non-fatal burden of tuberculosis by drug resistance and HIV status for 195 countries and territories from 1990 to 2016. Methods We analysed 15 943 site-years of vital registration data, 1710 site-years of verbal autopsy data, 764 site-years of sample-based vital registration data, and 361 site-years of mortality surveillance data to estimate mortality due to tuberculosis using the Cause of Death Ensemble model. We analysed all available data sources, including annual case notifications, prevalence surveys, population-based tuberculin surveys, and estimated tuberculosis cause-specific mortality to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how the burden of tuberculosis differed from the burden predicted by the Socio-demographic Index (SDI), a composite indicator of income per capita, average years of schooling, and total fertility rate. Findings Globally in 2016, among HIV-negative individuals, the number of incident cases of tuberculosis was 9·02 million (95% uncertainty interval [UI] 8·05–10·16) and the number of tuberculosis deaths was 1·21 million (1·16–1·27). Among HIV-positive individuals, the number of incident cases was 1·40 million (1·01–1·89) and the number of tuberculosis deaths was 0·24 million (0·16–0·31). Globally, among HIV-negative individuals the age-standardised incidence of tuberculosis decreased annually at a slower rate (–1·3% [–1·5 to −1·2]) than mortality did (–4·5% [–5·0 to −4·1]) from 2006 to 2016. Among HIV-positive individuals during the same period, the rate of change in annualised age-standardised incidence was −4·0% (–4·5 to −3·7) and mortality was −8·9% (–9·5 to −8·4). Several regions had higher rates of age-standardised incidence and mortality than expected on the basis of their SDI levels in 2016. For drug-susceptible tuberculosis, the highest observed-to-expected ratios were in southern sub-Saharan Africa (13·7 for incidence and 14·9 for mortality), and the lowest ratios were in high-income North America (0·4 for incidence) and Oceania (0·3 for mortality). For multidrug-resistant tuberculosis, eastern Europe had the highest observed-to-expected ratios (67·3 for incidence and 73·0 for mortality), and high-income North America had the lowest ratios (0·4 for incidence and 0·5 for mortality). Interpretation If current trends in tuberculosis incidence continue, few countries are likely to meet the SDG target to end the tuberculosis epidemic by 2030. Progress needs to be accelerated by improving the quality of and access to tuberculosis diagnosis and care, by developing new tools, scaling up interventions to prevent risk factors for tuberculosis, and integrating control programmes for tuberculosis and HIV

Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950.Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950

Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita