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Background: India reported first laboratory-confirmed case of coronavirus disease 2019 (COVID-19) on 30 January from Kerala. Media surveillance is useful to capture unstructured information about outbreaks. We established media surveillance and described the characteristics of the COVID-19 cases, clusters, deaths by time, place, and person during January–March 2020 in India. Methods: The media surveillance team of ICMR-National Institute of Epidemiology abstracted data from public domains of India's Central and State health ministries, online news and social media platforms for the period of January 31 to March 26, 2020. We collected data on person (socio-demographics, circumstances of travel/contact, clinical and laboratory), time (date/period of reported exposures; laboratory confirmation and death) and place (location). We drew epidemic curve, described frequencies of cases by age and gender. We described available details for identified clusters. Results: As of March 26, 2020, India reported 694 (Foreigners = 45, 6%) confirmed COVID-19 cases (Attack rate = 0.5 per million population) and 17 deaths (Fatality = 2.5%) from 21 States and 6 Union Territories. The cases were higher among 20–59 years of age (60 of 85) and male gender (65 of 107). Median age at death was 68 years (Range: 38–85 years). We identified 13 clusters with a total of 63 cases and four deaths among the first 200 cases. Conclusion: Surveillance of media sources was useful in characterizing the epidemic in the early phase. Hence, media surveillance should be integrated in the routine surveillance systems to map the events specially in context of new disease outbreaks.

Abstract Background Unintentional injuries account for 10% of deaths worldwide; the majority due to road traffic injuries, falls, drowning, poisoning and burns. Effective surveillance systems provide evidence for informed injury prevention and treatment and improve recovery outcomes. Our objectives were to review existing sources of unintentional injury data, and quality of the data on the burden, distribution, risk factors and trends of unintentional injuries in India and to describe strengths and limitations of health facility-based data for potential use in injury surveillance systems. Methods We searched national and international organisations’ websites to identify unintentional injury-related mortality and morbidity data sources in India. We reviewed and evaluated data collection methods for surveillance attributes recommended by World Health Organization (WHO). We visited health facilities at all levels from public and private sectors, emergency transport centres, insurance offices and police stations in settings reporting significant number of injuries. In these sites, we interviewed key stakeholders using an explorative approach on current data collection processes and challenges to establishing an injury surveillance system based on WHO guidelines. Results Major gaps were highlighted in injury mortality and morbidity data in India, including ill-defined causes of injury deaths and lack of standardisation in classification and coding. Site visits revealed that reporting standards of injuries varied, with issues around clarity of definitions, accountability, time points and lack of reporter/coder training. Major challenges were lack of dedicated staff and training. Conclusions There is an important need to build human resource capacity, integrate data sources, standardise and streamline data collected, ensure accountability and capitalise on digital health information systems including insurance databases.

Background: Injury is an increasingly important health problem particularly in developing countries like India. Community-based studies are of paramount importance to develop preventive measures. Not many community-based studies have been done to assess the burden and nature of injury in India and the State of Tamil Nadu. Methods: A systematic random sample of households was selected from each of two selected Health sub-centers. All adult members were interviewed with a semi-structured questionnaire to collect information on unintentional injuries in a 30-day recall period. For children below 5 years, a responsible adult member (mostly mother or father) of the family was interviewed. Results: Totally 2216 members were surveyed in 502 households. The overall incidence of unintentional injuries was 9.6 % [95% Confidence Interval (CI): 8.4, 10.9]. Incidence was lowest in 15-44 age-groups and highest in 0-4 age-group (8.7% Vs 12.2%). The incidence was high in male than female (χ²= 10.88; p <0.001). All reported injuries were nonfatal in nature. The common types of injuries were minor injuries, falls, animal and insect bites and traffic injuries. The incidence of minor injuries was high (3.4%) compared to other types like falls (2.9%) and animal bite (1.6%). No injury was reported due to accidental poisoning and drowning. Conclusions: The incidence of unintentional injuries was found to be low in the present study. However, further studies using larger and more representative samples are needed to delineate the problem of unintentional injuries and their risk factors in rural Tamil Nadu. [ABSTRACT FROM AUTHOR]

Background: Limited information is available about the risk factors associated with death among patients of influenza A (H1N1) in India. Aims: To describe the epidemiology of laboratory-confirmed influenza A (H1N1) patients and identify risk factors associated with death. Settings and Design: We reviewed the surveillance data of laboratory-confirmed patients in Tamil Nadu, India, for the year 2010. We conducted a case-control study by comparing 70 laboratory-confirmed A (H1N1) patients who died (cases) with 210 A (H1N1) patients who recovered (controls) to identify the risk factors for deaths. Materials and Methods: We interviewed the controls and immediate care-takers of the influenza patients who died to collect information about socio-demographic details and co-morbid conditions. We used an abstraction form to collect the information about the clinical details from the case records of the hospitals where the cases and controls received treatment. Statistical Analysis: We analysed the surveillance data by time, place and person. We conducted univariate and multivariate logistic regression analysis for identifying factors associated death. Results: During 2010, 1302 laboratory-confirmed cases were reported to the Tamil Nadu surveillance unit. Of these, 72 patients died (case fatality=5.5%). About 2/3 of the cases and 40% of the deaths were from three districts. On multivariate analysis, past history of diabetes, treatment in private hospitals, treatment with corticosteroids during illness, visit to >1 healthcare facility before laboratory confirmation and delay of >48 h in starting antivirals were found to be independently associated with the deaths. Conclusions: Influenza patients with previous history of diabetes, who had treatment with corticosteroids during illness, and started with antivirals after 48 h of onset of symptoms, were at higher risk of adverse outcome. In order to reduce the risk of death during future waves of influenza in Tamil Nadu, the physicians need to be sensitised regarding (1) higher risk of adverse outcomes among A (H1N1) patients with diabetes; (2) adherence to the national protocol for categorisation of cases; (3) prompt initiation of antivirals for severe cases; and (4) avoidance of systemic corticosteroids during management. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To study the epidemiology of Helicobacter pylori (H. pylori) infection according to age group. Methods: H. pylori infection data among 1 965 consecutive patients referred to the Endoscopy Unit collected at Sungai Petani Hospital for oesophagogastro-duodenoscopy (OGD). The patients were divided into 9 age groups (10–19, 20–29, 30–39, 40–49, 50–59, 60–69, 70–79, 80–89 and 90–99 years). In addition these groups were further divided into three minor group namely young adults (10–39), older adults (40–69) and geriatric groups (70–99). Results: Overall prevalence of infection of H. pylori was analyzed and found that the prevalence increase with age (P<0.05). When the patients divided by ethnic and gender group with age, prevalence rate among young adults and older adults significantly higher (P<0.05) compared to geriatric groups across all races and gender (P<0.05). Furthermore, significantly higher number of males were infected compared to female (P<0.05) but such trend was only observed among older adult groups. In addition, there is a significant differences in H. pylori infection prevalence rates among ethnic groups (highest in Indians adults, followed Chinese and low in Malays, P<0.05). Conclusions: The overall prevalence of H. pylori did increase with age group across ethnicity and gender, in Northern Peninsular Malaysia. [ABSTRACT FROM AUTHOR]

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Supplemental Digital Content is available in the text. Background: The MyCode Community Health Initiative (MyCode) is returning actionable results from whole exome sequencing. Familial hypercholesterolemia (FH) is an inherited condition characterized by premature cardiovascular disease. Methods: We used multiple methods to assess care in 28 MyCode participants who received FH results. Chart reviews were conducted on 23 individuals in the sample and 7 individuals participated semistructured interviews. Results: Chart reviews for 23 individuals with a Geisinger primary care provider found that 4 individuals (17% of 23) were at LDL-C (low-density lipoprotein cholesterol) goal (of either LDL-C <100 mg/dL for primary prevention and LDL-C <70 mg/dL for secondary prevention) and 17 individuals (74% of 23) were prescribed lipid-lowering therapy before genetic result disclosure. After disclosure of the genetic test result, 5 individuals (22% of 23) met their LDL-C goal and 18 individuals (78% of 23) were prescribed lipid-lowering therapy. Follow-up care about this result was not documented for 4 individuals (17% of 23). Changes to intensity of medication management were made for 8 individuals (47% of 17 individuals previously prescribed lipid-lowering therapy). Interviewed individuals (n=7) were not surprised by their result as all knew they had high cholesterol; however, individuals did not seem to discern FH as a separate condition from their high cholesterol. Conclusions: Among individuals receiving genetic diagnosis of FH, >25% had no changes to lipid-lowering therapy, despite not being at LDL-C goal and learning their high cholesterol is related to a genetic condition requiring more aggressive treatment. Individuals and clinicians may have an inadequate understanding of FH as a distinct condition requiring enhanced medical management. [ABSTRACT FROM AUTHOR]