RESUMO
BACKGROUND: A foodborne disease outbreak among wedding attendees from Makunsar village, Palghar district, Maharashtra state, India, was reported on February 18, 2018. OBJECTIVES: The outbreak investigation was conducted to find out the epidemiology of the outbreak and to identify the etiologic agent and risk factors. METHODS: A case-control study was carried out, where cases (patients), controls, and food handlers were interviewed and leftover foods were collected for culture. A case was defined as a person having vomiting or diarrhea (i.e., ≥3 loose stools within 24 h) who attended the wedding ceremony at Makunsar village, Palghar district, Maharashtra, on February 18, 2018. Attack rate and odds ratio (OR) were calculated with 95% confidence intervals (CIs). RESULTS: Out of 75 cases, 63% were female. Altogether, forty-two (56%) cases were hospitalized, and later on, all of them were discharged from hospital without any mortality. About 93%, 68%, 43%, and 41% of the cases reported with vomiting, nausea, abdominal pain, and diarrhea, respectively. The median incubation period was found to be 4 h (range: 2-8 h). Eating gaajar halwa (carrot pudding) was significantly associated with illness (OR: 12.8; 95% CI: 3.5-46). Gaajar halwa is prepared with khoa, a perishable milk product. The gaajar halwa culture yielded no growth. CONCLUSION: The case-patients' clinical presentation and incubation period were consistent with enterotoxin-producing Staphylococcus aureus as the probable etiologic agent. The epidemiologic investigation identified the probable etiologic agent and food source in a low-resource community setting. Community food handlers were educated on food preparation hygiene and safe storage measures to prevent future outbreaks.
Assuntos
Doenças Transmitidas por Alimentos , Gastroenterite , Estudos de Casos e Controles , Surtos de Doenças , Feminino , Doenças Transmitidas por Alimentos/epidemiologia , Gastroenterite/epidemiologia , Humanos , Índia/epidemiologia , MasculinoRESUMO
Background: Seasonal influenza causes significant morbidity and mortality, with an estimated 9.4 million hospitalisations and 290 000-650 000 respiratory related-deaths globally each year. Influenza can also cause mild illness, which is why not all symptomatic persons might necessarily be tested for influenza. To monitor influenza activity, healthcare facility-based syndromic surveillance for influenza-like illness is often implemented. Participatory surveillance systems for influenza-like illness (ILI) play an important role in influenza surveillance and can complement traditional facility-based surveillance systems to provide real-time estimates of influenza-like illness activity. However, such systems differ in designs between countries and contexts, making it necessary to identify their characteristics to better understand how they fit traditional surveillance systems. Consequently, we aimed to investigate the performance of participatory surveillance systems for ILI worldwide. Methods: We systematically searched four databases for relevant articles on influenza participatory surveillance systems for ILI. We extracted data from the included, eligible studies and assessed their quality using the Joanna Briggs Critical Appraisal Tools. We then synthesised the findings using narrative synthesis. Results: We included 39 out of 3797 retrieved articles for analysis. We identified 26 participatory surveillance systems, most of which sought to capture the burden and trends of influenza-like illness and acute respiratory infections among cohorts with risk factors for influenza-like illness. Of all the surveillance system attributes assessed, 52% reported on correlation with other surveillance systems, 27% on representativeness, and 21% on acceptability. Among studies that reported these attributes, all systems were rated highly in terms of simplicity, flexibility, sensitivity, utility, and timeliness. Most systems (87.5%) were also well accepted by users, though participation rates varied widely. However, despite their potential for greater reach and accessibility, most systems (90%) fared poorly in terms of representativeness of the population. Stability was a concern for some systems (60%), as was completeness (50%). Conclusions: The analysis of participatory surveillance system attributes showed their potential in providing timely and reliable influenza data, especially in combination with traditional hospital- and laboratory led-surveillance systems. Further research is needed to design future systems with greater uptake and utility.