Dataset Information

Performance of the Severe Acute Respiratory Illness Sentinel Surveillance System in Yemen: Mixed Methods Evaluation Study.

ABSTRACT:

Background

The national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks.

Objective

To ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen.

Methods

The updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%).

Results

As rated by the evaluators, the SARI surveillance system achieved its objectives. The system's flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as "excellent," and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as "good." The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support.

Conclusions

The SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities' (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.

SUBMITTER: Alkholidy GG

PROVIDER: S-EPMC8304118 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:The average life expectancy for people with a severe mental illness (SMI) such as schizophrenia or bipolar disorder is 15 to 20 years less than that for the population as a whole. Diabetes contributes significantly to this inequality, being 2 to 3 times more prevalent in people with SMI. Various risk factors have been implicated, including side effects of antipsychotic medication and unhealthy lifestyles, which often occur in the context of socioeconomic disadvantage and health care inequality. However, little is known about how these factors may interact to influence the risk of developing diabetes and poor diabetic outcomes, or how the organization and provision of health care may contribute. OBJECTIVE:This study aims to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with SMI. METHODS:This study will employ a concurrent mixed methods design combining the interrogation of electronic primary care health records from the Clinical Practice Research Datalink (CPRD GOLD) with qualitative interviews with adults with SMI and diabetes, their relatives and friends, and health care staff. The study has been funded for 2 years, from September 2017 to September 2019, and data collection has recently ended. RESULTS:CPRD and linked health data will be used to explore the association of sociodemographics, illness, and health care-related factors with both the development and outcomes of type 2 diabetes in people with SMI. Experiences of managing the comorbidity and accessing health care will be explored through qualitative interviews using topic guides informed by evidence synthesis and expert consultation. Findings from both datasets will be merged to develop a more comprehensive understanding of diabetes risks, interventions, and outcomes for people with SMI. Findings will be translated into recommendations for interventions and services using co-design workshops. CONCLUSIONS:Improving diabetes outcomes for people with SMI is a high-priority area nationally and globally. Understanding how risk factors combine to generate high prevalence of diabetes and poor diabetic outcomes for this population is a necessary first step in developing health care interventions to improve outcomes for people with diabetes and SMI. TRIAL REGISTRATION:ClinicalTrials.gov NCT03534921; https://clinicaltrials.gov/ct2/show/NCT03534921.

Project description:ObjectivesTo establish a hospital-based platform to explore the epidemiological and clinical characteristics of patients screened for COVID-19.DesignHospital-based surveillance.SettingThis study was conducted in four selected hospitals in Bangladesh during 10 June-31 August 2020.ParticipantsIn total, 2345 patients of all age (68% male) attending the outpatient and inpatient departments of surveillance hospitals with any one or more of the following symptoms within last 7 days: fever, cough, sore throat and respiratory distress.Outcome measuresThe outcome measures were COVID-19 positivity and mortality rate among enrolled patients. Pearson's χ2 test was used to compare the categorical variables (sign/symptoms, comorbidities, admission status and COVID-19 test results). Regression analysis was performed to determine the association between potential risk factors and death.ResultsCOVID-19 was detected among 922 (39%) enrolled patients. It was more common in outpatients with a peak positivity in second week of July (112, 54%). The median age of the confirmed COVID-19 cases was 38 years (IQR: 30-50), 654 (71%) were male and 83 (9%) were healthcare workers. Cough (615, 67%) was the most common symptom, followed by fever (493, 53%). Patients with diabetes were more likely to get COVID-19 than patients without diabetes (48% vs 38%; OR: 1.5; 95% CI: 1.2 to 1.9). The death rate among COVID-19 positive was 2.3%, n=21. Death was associated with age ≥60 years (adjusted OR (AOR): 13.9; 95% CI: 5.5 to 34), shortness of breath (AOR: 9.7; 95% CI: 3.0 to 30), comorbidity (AOR: 4.8; 95% CI: 1.1 to 21.7), smoking history (AOR: 2.2, 95% CI: 0.7 to 7.1), attending the hospital in <2 days of symptom onset due to critical illness (AOR: 4.7; 95% CI: 1.2 to 17.8) and hospital admission (AOR: 3.4; 95% CI: 1.2 to 9.8).ConclusionsCOVID-19 positivity was observed in more than one-third of patients with suspected COVID-19 attending selected hospitals. While managing such patients, the risk factors identified for higher death rates should be considered.

Project description:BackgroundLimited information exists on the epidemiology of acute febrile respiratory illnesses in tropical South American countries such as Venezuela. The objective of the present study was to examine the epidemiology of influenza-like illness (ILI) in two hospitals in Maracay, Venezuela.Methodology/principal findingsWe performed a prospective surveillance study of persons with ILI who presented for care at two hospitals in Maracay, Venezuela, from October 2006 to December 2010. A respiratory specimen and clinical information were obtained from each participant. Viral isolation and identification with immunofluorescent antibodies and molecular methods were employed to detect respiratory viruses such as adenovirus, influenza A and B, parainfluenza, and respiratory sincytial virus, among others. There were 916 participants in the study (median age: 17 years; range: 1 month--86 years). Viruses were identified in 143 (15.6%) subjects, and one participant was found to have a co-infection with more than one virus. Influenza viruses, including pandemic H1N1 2009, were the most frequently detected pathogens, accounting for 67.4% (97/144) of the viruses detected. Adenovirus (15/144), parainfluenza virus (13/144), and respiratory syncytial virus (11/144) were also important causes of ILI in this study. Pandemic H1N1 2009 virus became the most commonly isolated influenza virus during its initial appearance in 2009. Two waves of the pandemic were observed: the first which peaked in August 2009 and the second--higher than the preceding - that peaked in October 2009. In 2010, influenza A/H3N2 re-emerged as the most predominant respiratory virus detected.Conclusions/significanceInfluenza viruses were the most commonly detected viral organisms among patients with acute febrile respiratory illnesses presenting at two hospitals in Maracay, Venezuela. Pandemic H1N1 2009 influenza virus did not completely replace other circulating influenza viruses during its initial appearance in 2009. Seasonal influenza A/H3N2 was the most common influenza virus in the post-pandemic phase.

Project description:The World Health Organization and others warn that substandard and falsified medicines harm health and waste money, especially in low- and middle-income countries. However, no country has measured the market-wide extent of the problem, and no standardized methods exist to estimate the prevalence of either substandard or falsified medicines. This is, in part, because the task seems overwhelming; medicine markets are huge and diverse, and testing medicines is expensive. Many countries do operate some form of postmarket surveillance of medicine, but their methods and goals differ. There is currently no clear guidance on which surveillance method is most appropriate to meet specific public health goals. In this viewpoint, we aimed to discuss the utility of both case finding and risk-based sentinel surveillance for substandard and falsified medicines, linking each to specific public health goals. We posit that choosing the system most appropriate to the goal, as well as implementing it with a clear understanding of the factors driving the production and sale of substandard and falsified medicines, will allow for surveillance resources to be concentrated most efficiently. We adapted principles used for disease outbreak responses to suggest a case-finding system that uses secondary data to flag poor-quality medicines, proposing risk-based indicators that differ for substandard and falsified medicines. This system potentially offers a cost-effective way of identifying "cases" for market withdrawal, enhanced oversight, or another immediate response. We further proposed a risk-based sentinel surveillance system that concentrates resources on measuring the prevalence of substandard and falsified medicines in the risk clusters where they are most likely to be found. The sentinel surveillance system provides base data for a transparent, spreadsheet-based model for estimating the national prevalence of substandard and falsified medicines. The methods we proposed are based on ongoing work in Indonesia, a large and diverse middle-income country currently aiming to achieve universal health coverage. Both the case finding and the sentinel surveillance system are designed to be adaptable to other resource-constrained settings.