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Estimation of undetected symptomatic and asymptomatic cases of COVID-19 infection and prediction of its spread in the USA.

ABSTRACT: The reported COVID-19 cases in the United States of America have crossed over 10 million and a large number of infected cases are undetected whose estimation can be done if country-wide antibody testing is performed. In this study, we estimate this undetected fraction of the population by a modeling and simulation approach. We employ an epidemic model SIPHERD in which three categories of infection carriers, symptomatic, purely asymptomatic, and exposed are considered with different transmission rates that are taken dependent on the social distancing conditions, and the detection rate of the infected carriers is taken dependent on the tests done per day. The model is first validated for Germany and South Korea and then applied for prediction of the total number of confirmed, active and dead, and daily new positive cases in the United States. Our study predicts the possible outcomes of the infection if social distancing conditions are relaxed or kept stringent. We estimate that around 30.1 million people are already infected, and in the absence of any vaccine, 66.2 million (range: 64.3-68.0) people, or 20% (range: 19.4-20.5) of the population will be infected by mid-February 21 if social distancing conditions are not made stringent. We find the infection-to-fatality ratio to be 0.65% (range: 0.63-0.67).

SUBMITTER: Mahajan A

PROVIDER: S-EPMC8013178 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeThe current global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), led to the investigation with clinical, biochemical, immunological, and genomic characterization from patients to understand the pathophysiology of viral infection.MethodsSamples were collected from six asymptomatic and six symptomatic SARS-CoV-2-confirmed hospitalized patients in Bhubaneswar, Odisha, India. Clinical details, biochemical parameters, and treatment regimen were collected from a hospital; viral load was determined by RT-PCR; and the levels of cytokines and circulating antibodies in plasma were assessed by Bio-Plex and isotyping, respectively. In addition, whole-genome sequencing of viral strains and mutational analysis were carried out.ResultsAnalysis of the biochemical parameters highlighted the increased levels of C-reactive protein (CRP), lactate dehydrogenase (LDH), serum SGPT, serum SGOT, and ferritin in symptomatic patients. Symptomatic patients were mostly with one or more comorbidities, especially type 2 diabetes (66.6%). The virological estimation revealed that there was no significant difference in viral load of oropharyngeal (OP) samples between the two groups. On the other hand, viral load was higher in plasma and serum samples of symptomatic patients, and they develop sufficient amounts of antibodies (IgG, IgM, and IgA). The levels of seven cytokines (IL-6, IL-1α, IP-10, IL-8, IL-10, IFN-α2, IL-15) were found to be highly elevated in symptomatic patients, while three cytokines (soluble CD40L, GRO, and MDC) were remarkably higher in asymptomatic patients. The whole-genome sequence analysis revealed that the current isolates were clustered with 19B, 20A, and 20B clades; however, 11 additional changes in Orf1ab, spike, Orf3a, Orf8, and nucleocapsid proteins were acquired. The D614G mutation in spike protein is linked with higher virus replication efficiency and severe SARS-CoV-2 infection as three patients had higher viral load, and among them, two patients with this mutation passed away.ConclusionsThis is the first comprehensive study of SARS-CoV-2 patients from India. This will contribute to a better understanding of the pathophysiology of SARS-CoV-2 infection and thereby advance the implementation of effective disease control strategies.

Project description:The coronavirus disease 2019 (COVID-19) cases could be symptomatic or asymptomatic. We (1) characterized and analyzed data collected from the first cohort of reverse transcriptase polymerase chain reaction (RT-PCR)-confirmed COVID-19 cases reported in the Emirate of Abu Dhabi, United Arab Emirates, according to the symptomatic state, and (2) identified factors associated with the symptomatic state. The association between the symptomatic state and testing positive in three subsequent RT-PCR testing rounds was also quantified. Between February 28 and April 8, 2020, 1,249 cases were reported. Sociodemographic characteristics, working status, travel history, and chronic comorbidities of 791 cases were analyzed according to the symptomatic state (symptomatic or asymptomatic). After the first confirmatory test, the results of three subsequent tests were analyzed. The mean age of the 791 cases was 35.6 ± 12.7 years (range: 1-81). Nearly 57.0% of cases were symptomatic. The two most frequent symptoms were fever (58.0%) and cough (41.0%). Symptomatic cases (mean age 36.3 ± 12.6 years) were significantly older than asymptomatic cases (mean age 34.5 ± 12.7 years). Compared with nonworking populations, working in public places (adjusted odds ratio (aOR), 1.76, 95% confidence interval (95% CI): 1.11-2.80), healthcare settings (aOR, 2.09, 95% CI: 1.01-4.31), or in the aviation and tourism sectors (aOR, 2.24, 95% CI: 1.14-4.40) was independently associated with the symptomatic state. Reporting at least one chronic comorbidity was also associated with symptomatic cases (aOR, 1.76, 95% CI: 1.03-3.01). Compared with asymptomatic cases, symptomatic cases had a prolonged duration of viral shedding and consistent odds of ?2 positive COVID-19 tests result out of the three subsequent testing rounds. A substantial proportion of the diagnosed COVID-19 cases in the Emirate of Abu Dhabi were asymptomatic. Quarantining asymptomatic cases, implementing prevention measures, and raising awareness among populations working in high-risk settings are warranted.

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Estimation of undetected symptomatic and asymptomatic cases of COVID-19 infection and prediction of its spread in the USA.

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