Dataset Information

Robust estimation of SARS-CoV-2 epidemic in US counties.

ABSTRACT: The COVID-19 outbreak is asynchronous in US counties. Mitigating the COVID-19 transmission requires not only the state and federal level order of protective measures such as social distancing and testing, but also public awareness of time-dependent risk and reactions at county and community levels. We propose a robust approach to estimate the heterogeneous progression of SARS-CoV-2 at all US counties having no less than 2 COVID-19 associated deaths, and we use the daily probability of contracting (PoC) SARS-CoV-2 for a susceptible individual to quantify the risk of SARS-CoV-2 transmission in a community. We found that shortening by [Formula: see text] of the infectious period of SARS-CoV-2 can reduce around [Formula: see text] (or 78 K, [Formula: see text] CI: [66 K , 89 K ]) of the COVID-19 associated deaths in the US as of 20 September 2020. Our findings also indicate that reducing infection and deaths by a shortened infectious period is more pronounced for areas with the effective reproduction number close to 1, suggesting that testing should be used along with other mitigation measures, such as social distancing and facial mask-wearing, to reduce the transmission rate. Our deliverable includes a dynamic county-level map for local officials to determine optimal policy responses and for the public to better understand the risk of contracting SARS-CoV-2 on each day.

SUBMITTER: Li H

PROVIDER: S-EPMC8178310 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The reproductive number is an important metric that has been widely used to quantify the infectiousness of communicable diseases. The time-varying instantaneous reproductive number is useful for monitoring the real-time dynamics of a disease to inform policy making for disease control. Local estimation of this metric, for instance at a county or city level, allows for more targeted interventions to curb transmission. However, simultaneous estimation of local reproductive numbers must account for potential sources of heterogeneity in these time-varying quantities-a key element of which is human mobility. We develop a statistical method that incorporates human mobility between multiple regions for estimating region-specific instantaneous reproductive numbers. The model also can account for exogenous cases imported from outside of the regions of interest. We propose two approaches to estimate the reproductive numbers, with mobility data used to adjust incidence in the first approach and to inform a formal priori distribution in the second (Bayesian) approach. Through a simulation study, we show that region-specific reproductive numbers can be well estimated if human mobility is reasonably well approximated by available data. We use this approach to estimate the instantaneous reproductive numbers of COVID-19 for 14 counties in Massachusetts using CDC case report data and the human mobility data collected by SafeGraph. We found that, accounting for mobility, our method produces estimates of reproductive numbers that are distinct across counties. In contrast, independent estimation of county-level reproductive numbers tends to produce similar values, as trends in county case-counts for the state are fairly concordant. These approaches can also be used to estimate any heterogeneity in transmission, for instance, age-dependent instantaneous reproductive number estimates. As people are more mobile and interact frequently in ways that permit transmission, it is important to account for this in the estimation of the reproductive number.

Project description:Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to persist due to mutations resulting in newer, more infectious variants of concern. We aimed to leverage an ongoing private SARS-CoV-2 testing laboratory's infrastructure to monitor SARS-CoV-2 variants in two large California counties. Study enrollment was offered to adults aged 18 years or older in Los Angeles County and Riverside County who recently tested positive for SARS-CoV-2 with a polymerase chain reaction (PCR) assay. A cycle threshold value less than or equal to 30 cycles was considered a positive test for sequencing purposes. Within 5 days of study enrollment, clinician-monitored, self-collected oral fluid and anterior nares swab specimens were obtained from participants. Specimens were transported and stored at 8 °C or cooler. Samples underwent ribonucleic acid extraction, library preparation, and sequencing. SARS-CoV-2 lineages were identified using sequencing data. Participant and genomic data were analyzed using statistical tools and visualized with toolkits. The study was approved by Advarra Institutional Review Board (Pro00053729). From May 27, 2021 to September 9, 2021, 503 individuals were enrolled and underwent specimen collection. Of the 503 participants, 238 (47.3%) participants were women, 329 (63.6%) participants were vaccinated, and 221 (43.9%) participants were of Hispanic or Spanish origin. Of the cohort, 496 (98.6%) participants had symptoms at the time of collection. Among the 503 samples, 443 (88.1%) nasal specimens and 353 (70.2%) oral specimens yielded positive sequencing results. Over our study period, the prevalence of the Alpha variant of SARS-CoV-2 decreased (initially 23.1% [95% confidence interval (95% CI): 0-0.49%] to 0% [95% CI 0.0-0.0%]) as the prevalence of the Delta variant of SARS-CoV-2 increased (initially 33.3% [95% CI 0.0-100.0%] to 100.0% [95% CI 100.0-100.0%]). A strain that carried mutations of both Delta and Mu was identified. We found that outpatient SARS-CoV-2 variant surveillance could be conducted in a timely and accurate manner. The prevalence of different variants changed over time. A higher proportion of nasal specimens yielded results versus oral specimens. Timely and regional outpatient SARS-CoV-2 variant surveillance could be used for public health efforts to identify changes in SARS-CoV-2 strain epidemiology.

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Robust estimation of SARS-CoV-2 epidemic in US counties.

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