402. COVID-19 Infection in Nepal: Epidemiological Analysis from April 2020 to March 2021

Abstract Background In December 2019, SARS-CoV-2 or coronavirus disease 2019 (COVID-19) emerged from Wuhan, China. A global pandemic quickly unfolded, infecting >137 million people and causing >2.9 million deaths globally as of April 13, 2021. Before April 1, 2020, there were only five confirmed COVID-19 cases in Nepal. Like many countries around the world, the COVID-19 situation quickly escalated in Nepal. The purpose of this study was to determine the trends in COVID-19 cases and deaths in Nepal from April 2020 to March 2021. Methods We utilized epidemiological data from daily Situation Reports published by the Ministry of Health and Population (MOHP) of Nepal. Data were extracted or calculated from April 1, 2020 to March 31, 2021. Primary variables of interest were national and provincial daily cases, total cases, daily deaths, and total deaths. Results Between April 1, 2020 to March 31, 2021, there were 277,304 cases. October 2020 had the highest monthly cases with 92,926 cases. During the one-year study period, the infection rate was 915 cases per 100,000 people. The largest single-day new cases was October 21, 2020 with 5,743 cases, which is calculated to 19 cases per 100,000 people. There were a total of 3,030 deaths. The largest daily new deaths was November 4, 2020 with 43 cases. June 10, 2020 had the highest number of people in quarantine with 172,266 people. October 23, 2020 had the highest number of active cases with 46,329 cases. By March 31, 2021, the percent of mortality was 1.1%, active infection was 0.5%, and recovery was 98.4%. Conclusion Nepal had lower COVID-19 infection and case-fatality rates compared to other countries most affected by the pandemic. This was due to several factors, most notably early implementation of strict lockdown measures and closing of international borders on March 24, 2020 after the second confirmed COVID-19 case. As lockdown restrictions were lifted on July 7, 2020, COVID-19 cases and deaths in Nepal rose rapidly. As vaccination begun on January 27, 2021, cases started to slow down until the most recent outbreak coinciding with the second wave in its neighboring country, India. Now, infection and case-fatality rates in Nepal are at an all-time high, prompting further lockdowns on April 29, 2021. Disclosures All Authors: No reported disclosures

were TA positives. Of those negatives, 94% were TA SARS-CoV-2 negative with 2620 SWDs (average 7.5 days/person). There were no healthcare outbreaks related to HCWs allowed to return to work following this strategy.
Asymptomatic healthcare workers commonly tested positive for SARS-CoV-2 on day 2 from household exposure compared to other days Conclusion. Test-based strategy among asymptomatic HCWs with HRE reduced loss of workdays and helped limit staffing shortages. Majority of positive HCWs developed symptoms after positive SARS-CoV-2 testing, which may support allowing most fully vaccinated HCWs with no COVID-like symptoms to continue to work unless symptomatic.
Disclosures. Background. In order to mitigate the spread of SARS-CoV-2 and the COVID-19 pandemic, public health officials have recommended self-isolation, self-quarantine of exposed household contacts (HHC), and mask use to limit viral spread within households and communities. While household transmission of SARS-CoV-2 is common, risk factors for HHC transmission are poorly understood.
Methods. In this prospective cohort study, we enrolled 37 households with at least one reverse transcription polymerase chain reaction-confirmed (RT-PCR) COVID-19 index case from March 2020 -March 2021, in order to calculate secondary attack rates (SAR) and define risk factors for secondary infections. Participants were tested daily for SARS-CoV-2 via RT-PCR, using self-collected lower nasal samples. Households were followed until all members tested negative for seven consecutive days. We collected demographics, medical conditions, relationship to index case, and socioeconomic indicators. Subgroup data analysis was conducted and stratified by positivity status.
Conclusion. This study suggests that household transmission represents a key source of community-based infection of SARS-CoV-2. Allocating resources for education/training regarding prevention among infected individuals and their close contacts will be critical for control of future outbreaks of SARS-CoV-2.
Disclosures. Background. In December 2019, SARS-CoV-2 or coronavirus disease 2019 (COVID-19) emerged from Wuhan, China. A global pandemic quickly unfolded, infecting >137 million people and causing >2.9 million deaths globally as of April 13, 2021. Before April 1, 2020, there were only five confirmed COVID-19 cases in Nepal. Like many countries around the world, the COVID-19 situation quickly escalated in Nepal. The purpose of this study was to determine the trends in COVID-19 cases and deaths in Nepal from April 2020 to March 2021.
Methods. We utilized epidemiological data from daily Situation Reports published by the Ministry of Health and Population (MOHP) of Nepal. Data were extracted or calculated from April 1, 2020 to March 31, 2021. Primary variables of interest were national and provincial daily cases, total cases, daily deaths, and total deaths.
Results. Between April 1, 2020 to March 31, 2021, there were 277,304 cases. October 2020 had the highest monthly cases with 92,926 cases. During the one-year study period, the infection rate was 915 cases per 100,000 people. The largest single-day new cases was October 21, 2020 with 5,743 cases, which is calculated to 19 cases per 100,000 people. There were a total of 3,030 deaths. The largest daily new deaths was November 4, 2020 with 43 cases. June 10, 2020 had the highest number of people in quarantine with 172,266 people. October 23, 2020 had the highest number of active cases with 46,329 cases. By March 31, 2021, the percent of mortality was 1.1%, active infection was 0.5%, and recovery was 98.4%.
Conclusion. Nepal had lower COVID-19 infection and case-fatality rates compared to other countries most affected by the pandemic. This was due to several factors, most notably early implementation of strict lockdown measures and closing of international borders on March 24, 2020 after the second confirmed COVID-19 case. As lockdown restrictions were lifted on July 7, 2020, COVID-19 cases and deaths in Nepal rose rapidly. As vaccination begun on January 27, 2021, cases started to slow down until the most recent outbreak coinciding with the second wave in its neighboring country, India. Now, infection and case-fatality rates in Nepal are at an all-time high, prompting further lockdowns on April 29, 2021.
Disclosures. Background. The disease caused by SARS-CoV-2, COVID-19, has caused a global public health crisis. Reported mortality rates across the world vary by region, local population characteristics and healthcare systems. There is a paucity of data on COVID-19 in low and middle income countries (LMICs). Our objective is to describe the clinical characteristics of critically ill patients with COVID-19 in the Dominican Republic (DR) Methods. We performed a retrospective review of patients admitted to the intensive care unit (ICU) with severe COVID-19 from March to December 31, 2020, at a 295-bed tertiary teaching hospital in the DR. Clinical characteristics, demographics, comorbidities, management and outcomes were tabulated. Survival was categorized by age and comorbidities.
Results. A total of 382 patients were admitted to the ICU. The median age was 64 (range 14-97) and 64.3% (246) were male. Hypertension, diabetes, and obesity were the most common risk factors (Table 1). Corticosteroids were used in 91.6% (350), tocilizumab in 63% (82), and remdesivir in 31.6% (31). Antibacterials were used in 99.2% (379) of patients in the ICU. All-cause mortality in the ICU was 35.3% (135). Mortality was higher in older age groups ( Figure 1) and in patients with multiple coexisting comorbidities (Figure 2).   Conclusion. Hypertension, obesity and diabetes were common in critically ill patients with COVID-19 in the DR. Corticosteroids and tocilizumab were commonly used. Antibacterials were used in >99% of patients admitted to the ICU and may signal a target for future antimicrobial stewardship. Higher mortality rates were present in older age groups and those with multiple comorbidities. Risk of death increased drastically after age 40 and was comparative to those in advanced age groups. In patients with 4 comorbidities and above, mortality was more than three times higher.
Disclosures. Background. The COVID-19 pandemic created the most severe global education disruption in history. According to UNESCO, at the peak of the crisis over 1.6 billion learners in more than 190 countries were out of school. After one year, half of the world's student population is still affected by full or partial school closures. Here we investigated whether or not it is possible to build a multivariate score for dynamic school decision-making specially in scenarios without population-scale RT-PCR tests.
Methods. Normality rate is based on a COVID-19 risk matrix (Table 1). Total score (TS) is obtained by summing the risk scores for COVID-19, considering the six parameters of the pandemic in a city. The COVID-19 Normality Rate (CNR) is obtained by linear interpolation in such a way that a total score of 30 points is equivalent to a 100% possibility of normality and, in a city with only six total points would have zero percent chance of returning to normality: CNR = (TS -6)/24 (%). The criteria for opening and closing schools can be defined based on the percentages of return to normality (Table 2). Table 1. Limits for each parameter of the risk matrix and "normality" scores in relation to COVID-19: the lower the risk, higher is the "normality" score.