Allied Journal of Medical Research

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Short Communication - Allied Journal of Medical Research (2021) Volume 5, Issue 9

COVID-19 antibody

Mark Jack*

Department of Medical Research, Cairo University, Giza, Egypt

Corresponding Author:
Dr. Mark Jack
Department of Medical Research
Cairo University
Giza
Egypt
E-mail: [email protected]

Accepted date: 06 August, 2021

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Abstract

The first two cases of COVID-19 in Santa Clara County, California were identified in returning travelers on January 31 and on February 1, 2020, and the third case was identified four weeks later. In the following month, nearly 1,000 additional cases were identified in Santa Clara County, showing a pattern of rapid case increase reflective of community transmission as well as the scaling up of SARS-CoV-2 viral testing that was common across many communities globally

Description

The first two cases of COVID-19 in Santa Clara County, California were identified in returning travelers on January 31 and on February 1, 2020, and the third case was identified four weeks later. In the following month, nearly 1,000 additional cases were identified in Santa Clara County, showing a pattern of rapid case increase reflective of community transmission as well as the scaling up of SARS-CoV-2 viral testing that was common across many communities globally. In some countries, the rapid increase in COVID-19 case counts and hospitalizations has overwhelmed health systems and led to large reductions in social and economic activities [1]. The measures adopted to slow the spread of COVID-19 were justified by projected estimates of health care system capacity and case fatality rate. These projections suggested that, in the absence of strict measures to reduce transmission, the COVID-19 pandemic would overwhelm existing hospital bed and ICU capacity throughout the United States and lead to over 2 million deaths.

Measuring fatality rates and projecting the number of deaths depend on estimates of the total number of infections. To date, in the absence of seroprevalence surveys, estimates of the fatality rate have relied on the number of confirmed cases multiplied by an estimated factor representing unknown or asymptomatic cases to arrive at the number of infections. However, the magnitude of that factor is highly uncertain. Because the implications of infection fatality rate and projected deaths are large, the extent of COVID-19 infection underascertainment (the multiplier used to arrive from cases to infections) has been a topic of great interest and provided estimates of the number of infections about 1-6-fold higher than the number of cases [2]. The extent of infection underascertainment has been difficult to assess because of three biasing processes: (i) cases have been diagnosed with PCRbased tests, which do not provide information about resolved infections; (ii) the majority of cases tested early in the course of the epidemic have been acutely ill and highly symptomatic, while most asymptomatic or mildly symptomatic individuals have not been tested; and (iii) PCR-based testing rates have been highly variable across contexts and over time, leading to noisy relationships between the number of cases and infections [3]. If, in the absence of interventions, the epidemic’s early doubling time is estimated to be four days, then by February 27th, 2020, when the third case was identified in Santa Clara County, the county may have already had 256 infections.

At the time of this study, Santa Clara County had the largest number of confirmed cases of any county in Northern California [4]. The county also had several of the earliest known cases of COVID-19 in the state including one of the first presumed cases of community-acquired disease making it an especially appropriate location to test a population-level sample for the presence of active and past infections.

On April 3rd and 4th, 2020 we conducted a survey of residents of Santa Clara County to measure the seroprevalence of antibodies to SARS-CoV-2 and better approximate the number of infections. Our goal is to provide new and well-measured data for informing epidemic models, projections, and public policy decisions [5].

References

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