Hospital-Based Contact Tracing of Patients With COVID-19 and Health Care Workers During the COVID-19 Pandemic in Eastern India: Cross-sectional Study.

BACKGROUND: The contact tracing and subsequent quarantining of health care workers (HCWs) are essential to minimizing the further transmission of SARS-CoV-2 infection and mitigating the shortage of HCWs during the COVID-19 pandemic situation. OBJECTIVE: This study aimed to assess the yield of contact tracing for COVID-19 cases and the risk stratification of HCWs who are exposed to these cases. METHODS: This was an analysis of routine data that were collected for the contact tracing of COVID-19 cases at the All India Institute of Medical Sciences, Bhubaneswar, in Odisha, India. Data from March 19 to August 31, 2020, were considered for this study. COVID-19 cases were admitted patients, outpatients, or HCWs in the hospital. HCWs who were exposed to COVID-19 cases were categorized, per the risk stratification guidelines, as high-risk contacts or low-risk contacts. RESULTS: During contact tracing, 3411 HCWs were identified as those who were exposed to 360 COVID-19 cases. Of these 360 cases, 269 (74.7%) were either admitted patients or outpatients, and 91 (25.3%) were HCWs. After the risk stratification of the 3411 HCWs, 890 (26.1%) were categorized as high-risk contacts, and 2521 (73.9%) were categorized as low-risk contacts. The COVID-19 test positivity rates of high-risk contacts and low-risk contacts were 3.8% (34/890) and 1.9% (48/2521), respectively. The average number of high-risk contacts was significantly higher when the COVID-19 case was an admitted patient (number of contacts: mean 6.6) rather than when the COVID-19 case was an HCW (number of contacts: mean 4.0) or outpatient (number of contacts: mean 0.2; P=.009). Similarly, the average number of high-risk contacts was higher when the COVID-19 case was admitted in a non-COVID-19 area (number of contacts: mean 15.8) rather than when such cases were admitted in a COVID-19 area (number of contacts: mean 0.27; P<.001). There was a significant decline in the mean number of high-risk contacts over the study period (P=.003). CONCLUSIONS: Contact tracing and risk stratification were effective and helped to reduce the number of HCWs requiring quarantine. There was also a decline in the number of high-risk contacts during the study period. This indicates the role of the implementation of hospital-based, COVID-19-related infection control strategies. The contact tracing and risk stratification approaches that were designed in this study can also be implemented in other health care settings.

Scrutiny of COVID-19 response strategies among severely affected European nations.

Although the health care systems in Europe are considered the global benchmark, European nations were severely affected by the coronavirus disease 2019 (COVID-19) pandemic. This manuscript aimed to examine the strategies implemented to combat the COVID-19 pandemic by France, the United Kingdom, Spain, Italy, Germany, and Russia and their outcomes in terms of the number of cases, testing, and deaths. This is the first review of its kind that extensively analyzes the preparedness, mitigation, and response strategies against the COVID-19 pandemic adopted by these nations. This paper further suggests a strategic preparedness model for future pandemics. From the analysis, we found that a decentralized approach, prompt decision-making and timely execution, coordination between local health authorities, and public participation in the implementation of strategies could substantially reduce the case fatality rate. Nations with a high percentage of gross domestic product invested in the health sector, as well as more nurses, physicians, hospital beds, intensive care unit beds, and ventilators, better managed the pandemic. Instead, nations that postponed their pandemic response by delaying tracking, tracing, testing, quarantine, and lockdown were badly affected. The lessons learned from the present pandemic could be used as a guide to prepare for further pandemics.

The human milk microbiome: who, what, when, where, why, and how?

Human milk (HM) contains an incredible array of microorganisms. These likely contribute to the seeding of the infant gastrointestinal microbiome, thereby influencing infant immune and metabolic development and later-life health. Given the importance of the HM microbiota in this context, there has been an increase in research efforts to characterize this in different populations and in relation to different maternal and infant characteristics. However, despite a decade of intensive research, there remain several unanswered questions in this field. In this review, the "5 W+H" approach (who, what, when, where, why, and how) is used to comprehensively describe the composition, function, and origin of the HM microbiome. Here, existing evidence will be drawn together and critically appraised to highlight avenues for further research, both basic and applied. Perhaps the most interesting of these is the potential to modulate the HM microbiome using pre/probiotics or dietary interventions. Another exciting possibility is the personalization of donor milk for women with insufficient supply. By gaining a deeper understanding of the HM microbiome, opportunities to intervene to optimize infant and lifelong health may be identified.

Hospital based contact tracing of COVID-19 patients and health care workers and risk stratification of exposed health care workers during the COVID-19 Pandemic in Eastern India

IntroductionContact tracing and subsequent quarantining of Health Care Workers (HCWs) is essential to minimize further transmission of COVID-19 infection. In this study, we have reported the yield of Contact Tracing of COVID-19 Patients and HCWs and risk stratification of exposed HCWs. MethodologyThis is a secondary analysis of routine data collected for contact tracing from 19th March to 31st August 2020 at All India Institute of Medical Sciences, Bhubaneswar, Odisha, India. HCWs exposed to COVID-19 infections were categorized as per the risk stratification guidelines and the high-risk contacts were quarantined for 14 days and tested on 7th day from last day of exposure. The low risk contacts were encouraged to closely monitor their symptoms while continuing to work. ResultsOut of 3411 HCWs exposed to COVID 19 patients (n=269) and HCWs (n=91), 890 (26.1%) were high risk contacts and 2521 (73.9%) were low risk contacts. The test positivity rate of high-risk contact was 3.82% and for low risk contact was 1.90%. Average number of high-risk contacts was significantly higher; for admitted patients (6.6) as compared to HCWs (4.0) and outpatients (0.2), p value = 0.009; for patients admitted in non-COVID areas (15.8) as compared to COVID areas (0.27), p value < 0.001; and when clustering of cases was present (14.3) as compared to isolated cases (8.2); p value < 0.001. Trend analysis (15 days block period) showed a significant decline in number of mean numbers of high-risk contacts during the study period. ConclusionContact tracing and risk stratification was effective and helped in reducing the number of HCWs going for quarantine. There was also a decline in high-risk contacts during study period suggesting role of implementation of hospital based COVID related infection control strategies. This contact tracing and risk stratification approach designed in the current study can also be implemented in other healthcare settings.