Estimating the impact of lockdown on COVID-19 cases in Pune, Maharashtra

Background: The COVID-19 pandemic commenced in China in December 2019 and has since become a major public health problem. To slow this down, countries went into lockdown with different levels of restrictions on movement and mandatory home confinement except for essential requirements and services. It effectively decelerated the pandemic by strengthening the healthcare system and thus averted lakhs of cases and saved thousands of lives. The aim of this study is to analyze statistically that the lockdown plays an important role in preventing COVID-19 and its impact on number of cases per day in Pune.Methods: This record based descriptive study is conducted after secondary data analysis of number of new cases of COVID-19 per day from the period 27 Apr to 03 Sep 2020 in Pune. Crowdsourced line listing of COVID-19 cases in Pune was obtained from https://www.covid19india.org/ which is Govt portal of COVID data and freely accessible. The data was thus analyzed to calculate effective reproduction number (Reff), growth rate and doubling time.Results: On plotting weekly reported number of COVID-19 cases, no specific impact of lockdown on COVID-19 cases in Pune were noticed. Reff when plotted on the timeline shows a decline post lockdown. Growth rate also shows a slight declining trend post lockdown.Conclusions: The importance of lockdown has been quantitatively confirmed to be effective in combating the spread of COVID-19 cases, focus should be placed on its effective implementation by the masses.

Patients with Positive Glutamine Dehydrogenase (GDH) Antigen/Toxin and Toxin Negative/PCR Positive Patients: A Comparison

Background: A multistep algorithm using GDH antigen plus toxin with a reflex PCR is an acceptable method for detecting CDI. The use of the PCR in discordant cases can identify those patients who are colonized from those patients who have nontoxogenic strains of C. difficile. Identification of discordant patients has infection prevention implications. Treatment is not recommended for patients colonized with C. difficile. Methods: A line listing of patients with positive hospital-onset antigen/toxin positive and discordant PCR positive was created. Demographic information was extracted from medical records and the 2 cohorts were compared. Results: There were 59 discordant and 44 positive cases HO CDI cases from October 2017 through September 2019: (1) There was no difference in age and sex between the 2 groups. (2) Positive patients tended to have 3 loose stools before and after testing (57% vs 27%; P = .026). (3) Overall, 82% of positive patients had 1 of 3 signs or symptoms (leukocytosis, abdominal pain, and temperature >38°C) consistent with CDI compared to 66% of discordant patients (P = .038), and 55% of positive patients were more likely to have 2 of 3 signs or symptoms of CDI compared to 17% of discordant patients (P = .00003). (4) Also, 46% of discordant patients were either on the oncology ward or ICU compared to 32% of positive patients (P = .764). (5) There was no difference between in discordant compared to positive patients in non-CDI antimicrobial therapy within 7 days of CDI test submission (81% vs 84%, respectively). Conclusions: (1) Screening for CDI testing should include 3 loose stools and at least 2 of 3 signs or symptoms of CDI. (2) Discordant cases most likely represents colonization because only 17% of discordant patients had 2 of 3 CDI signs or symptoms at presentation. (3) Discordant cases without clinical features of CDI should not receive treatment to minimize antibiotic exposure. (4) Identification of discordant patients have infection prevention ramifications because CD can be indirectly transmitted by colonized patients; therefore, using PCR in addition to toxin testing is favored. (5) Antimicrobial therapy highly associated with CDI should be avoided, should antimicrobial therapy be necessary in PCR-positive discordant patients.Funding: NoneDisclosures: None

Estimates of outbreak-specific SARS-CoV-2 epidemiological parameters from genomic data

We estimate the basic reproductive number and case counts for 15 distinct SARS-CoV-2 outbreaks, distributed across 10 countries and one cruise ship, based solely on phylodynamic analyses of genomic data. Our results indicate that, prior to significant public health interventions, the reproductive numbers for a majority (10) of these outbreaks are similar, with median posterior estimates ranging between 1.4 and 2.8. These estimates provide a view which is complementary to that provided by those based on traditional line listing data. The genomic-based view is arguably less susceptible to biases resulting from differences in testing protocols, testing intensity, and import of cases into the community of interest. In the analyses reported here, the genomic data primarily provides information regarding which samples belong to a particular outbreak. We observe that once these outbreaks are identified, the sampling dates carry the majority of the information regarding the reproductive number. Finally, we provide genome-based estimates of the cumulative case counts for each outbreak, which allow us to speculate on the amount of unreported infections within the populations housing each outbreak. These results indicate that for the majority (7) of the populations studied, the number of recorded cases is much bigger than the estimated cumulative case counts, suggesting the presence of unsequenced pathogen diversity in these populations.

Household Secondary Attack Rate in Gandhinagar district of Gujarat state from Western India

Objectives: Current retrospective study aims to evaluate household Secondary Attack Rate (SAR) of COVID-19 in Gandhinagar (rural) district of Gujarat, India. Methods: Line-listing of 486 laboratory-confirmed patients, tested between 28th March to 2nd July was collected, out of them 80 (15% of overall sample) cases were randomly selected. Demographic, clinical and household details of cases were collected through telephonic interview. During interview 28 more patients were identified from the same household and were added accordingly. So, study included 74 unrelated cluster of households with 74 primary cases and 386 close contacts. Results: SAR in household contacts of COVID-19 in Gandhinagar was 8.8%. Out of 108, 8 patients expired (7.4%), where higher mortality was observed in primary cases (9.5%) as compared to secondary cases (3%). Occupational analysis showed that majority of the secondary cases (88%) were not working and hence had higher contact time with patient. No out-of-pocket expenditure occurred in 94% of the patients, in remaining 6% average expenditure of 1,49,633INR (2027 USD) was recorded. Conclusions: Key observations from the study are 1) SAR of 8.8% is relatively low and hence home isolation of the cases can be continued 2) Primary case is more susceptible to fatal outcome as compared to secondary cases 3) Government has covered huge population of the COVID-19 patients under cost protection. However, more robust studies with larger datasets are needed to further validate the findings.

Investigation of the food poisoning outbreak in girls hostel of medical college in Punjab

Background: Food safety is intricately woven with food security and nutrition. The “in‑living personnel” constitute a high‑risk group for food poisoning because of community kitchen practices. Quick response and action are vital to limit the morbidity and spread of the disease.Methods: A retrospective cohort study was conducted to investigate the food poisoning outbreak in private medical college. After the initial information of the sudden cases of vomiting and diarrhoea from girls’ hostel, epidemiological case sheet was developed for collecting the information from students. A line listing of all the probable cases was done. Common food items were identified. An environmental data recording was done. Attack rate, attributable risk and relative risk with 95% confidence interval were calculated for each food item to establish an association with the illness.Results: Out of the 97 students, who consumed the dinner, 8 girls presented with severe symptoms of the gastrointestinal upset along with other bodily symptoms, 60 students showed mild symptoms and 29 students did not show any of the symptoms of the disease. After analysis, palak paneer was found to be the food responsible for outbreak with most probable cause of contamination with Staph auerus.Conclusions: It has been found out in this investigation that whenever the sanitation conditions of the cooking area were compromised and negligence was played at the part of food handlers - it has always increased the probability of such outbreaks and sufferings of the people.

Identifying Non-traditional Epidemic Disease Risk Factors associated to major Health Events from WHO and World Bank Open Data

ObjectivesHealth events emerge from a multifactorial milieu involving host, community, environment, and pathogen factors. Therefore, developing accurate forecasting models to improve epidemic prediction towards better prevention and capabilities management is a complex task. Here, we describe an exploratory analysis to identify non-health risk factors that could improve the forecast and events risk signals using a feasible and practical approach by combining surveillance report data with non-health data from open data sources.MethodsA line listing was developed using information from the World Health Organization Disease Outbreaks News from 2016-2018. A database was created merging the line listing data with non-health indicators from the World Bank. Poisson regression models employing forward imputations were used to establish relationships and predict values over the dependent variable (health event frequency); which are the health events reported by each country to WHO during 2016-2018.FindingsThe resulting regression model provided evidence that changes in non-health factors important to community experiences impact the risk of the number of major health events that a country could experience. Three non-health indicators (extrinsic factors) were associated significantly to event frequency (population urban change, gross domestic product change per capita—a novel factor, and average forest area). An exploratory analysis of the current COVID-19 pandemic suggested similar associations, but confounding by global disease burden is likely.ConclusionContinued development of forecasting approaches capturing available whole-of-society extrinsic factors (non-health factors); could improve the risk management process through earlier hazard identification, and as importantly inform strategic decision processes in multisectoral strategies to preventing, detecting, and responding to pandemic-threat events.

A cross sectional study on nutritional status and dental caries among rural preschool children of Sullia taluk, Karnataka

Background: A double burden of malnutrition in children, in the form of undernutrition and obesity exists in our world. Poverty and various other sociocultural factors act as important determinants of malnutrition. There exist varying prevalence rates in different places. Under nutrition has also a role in dental caries. The objective of this study was to find the prevalence of malnutrition and dental caries among children going to Anganwadi’s in rural Sullia taluk of Karnataka. Methods: Line listing of Anganwadi children was done and by random sampling method, 205 children were selected for study. Nutritional status was assessed by anthropometric measurements and dental examination done according to WHO standards. Results: The prevalence of underweight, wasting and stunting were 27%, 11% and 40% respectively. 49% of children studied had dental caries. Conclusions: According to the classification for assessing severity of malnutrition by prevalence ranges among children, the study area is classified as a high prevalence area for malnutrition according to WHO. Dental caries was present in 49.27% of the children.

Using NC DETECT for Comprehensive Morbidity Surveillance on Poisoning and Overdose

Twelve new locally defined case definitions were added to NC DETECT in May and June 2014 to facilitate timely surveillance for poisoning and overdose in North Carolina. The case definitions cover acute alcohol poisoning, poisoning, unintentional poisoning, heroin overdose, medication or drug overdose, methadone overdose, opioid overdose, prescription opioid analgesic overdose, Narcan/naloxone, and unintentional medication or drug overdose. Authorized users can monitor trends and review line listing details for their jurisdictions and compare their counties at the aggregate level to other counties and the state.