BackgroundThe United States' COVID-19 epidemic has grown extensively since February 2020, with substantial associated hospitalizations and mortality; New York State (NYS) has emerged as the national epicenter. We report on the extent of testing and test results during the month of March in NYS, along with risk factors, outcomes, and household prevalence among initial cases subject to indepth investigations. MethodsSpecimen collection for COVID-19 testing was conducted in healthcare settings, community-based collection sites, and by home testing teams. Information on demographics, risk factors, and hospital outcomes of cases was obtained through epidemiological investigations and an electronic medical records match, and summarized descriptively. Active testing of initial case's households enabled estimation of household prevalence. ResultsDuring March In NYS, outside of New York City, a total of 47,326 persons tested positive for SARS-CoV-2, out of 141,495 tests (33% test-positive), with the highest number of cases located in the metropolitan region counties. Among 229 initial cases diagnosed through March 12, by March 30 13% were hospitalized and 2% died. Testing conducted among 498 members of these case's households found prevalent infection among 57%; excluding first-reported cases 38%. In these homes, we found a significant age gradient in prevalence, from 23% among those <5 years to 68% among those ≥65 years (p<.0001). ConclusionsNew York State faced a substantial and increasing COVID-19 outbreak during March 2020. The earliest cases had high levels of infection in their households and by the end of the month, the risks of hospitalization and death were high.

Innovative monitoring approaches are needed to track the coronavirus disease 2019 (COVID-19) epidemic and potentially assess the impact of community mitigation interventions. We present temporal data on influenza-like illness, influenza diagnosis, and COVID-19 cases for all 4 regions of New York State through the first 6 weeks of the outbreak.

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Single-arm trials have played a major role in assessing the efficacy of interferon-free antiviral regimens for hepatitis C genotype 1. To facilitate evidence synthesis, we have devised methods to integrate single-arm evidence into the network meta-analysis (NMA) framework to indirectly compare interferon-free and interferon-containing antiviral regimens. Methods: We conducted a system