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1.
J Occup Environ Med ; 65(3): 193-202, 2023 03 01.
Article in English | MEDLINE | ID: covidwho-2261257

ABSTRACT

OBJECTIVE: On September 13, 2021, teleworking ended for New York City municipal employees, and Department of Education employees returned to reopened schools. On October 29, COVID-19 vaccination was mandated. We assessed these mandates' short-term effects on disease transmission. METHODS: Using difference-in-difference analyses, we calculated COVID-19 incidence rate ratios (IRRs) among residents 18 to 64 years old by employment status before and after policy implementation. RESULTS: IRRs after (September 23-October 28) versus before (July 5-September 12) the return-to-office mandate were similar between office-based City employees and non-City employees. Among Department of Education employees, the IRR after schools reopened was elevated by 28.4% (95% confidence interval, 17.3%-40.3%). Among City employees, the IRR after (October 29-November 30) versus before (September 23-October 28) the vaccination mandate was lowered by 20.1% (95% confidence interval, 13.7%-26.0%). CONCLUSIONS: Workforce mandates influenced disease transmission, among other societal effects.


Subject(s)
COVID-19 , Humans , Adolescent , Young Adult , Adult , Middle Aged , New York City/epidemiology , COVID-19 Vaccines , Schools , Vaccination
2.
Sci Adv ; 8(4): eabm0300, 2022 Jan 28.
Article in English | MEDLINE | ID: covidwho-2287593

ABSTRACT

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

3.
J Infect Dis ; 227(4): 533-542, 2023 02 14.
Article in English | MEDLINE | ID: covidwho-2244138

ABSTRACT

BACKGROUND: Evidence is accumulating of coronavirus disease 2019 (COVID-19) vaccine effectiveness among persons with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: We evaluated the effect against incident SARS-CoV-2 infection of (1) prior infection without vaccination, (2) vaccination (2 doses of Pfizer-BioNTech COVID-19 vaccine) without prior infection, and (3) vaccination after prior infection, all compared with unvaccinated persons without prior infection. We included long-term care facility staff in New York City aged <65 years with weekly SARS-CoV-2 testing from 21 January to 5 June 2021. Test results were obtained from state-mandated laboratory reporting. Vaccination status was obtained from the Citywide Immunization Registry. Cox proportional hazards models adjusted for confounding with inverse probability of treatment weights. RESULTS: Compared with unvaccinated persons without prior infection, incident SARS-CoV-2 infection risk was lower in all groups: 54.6% (95% confidence interval, 38.0%-66.8%) lower among unvaccinated, previously infected persons; 80.0% (67.6%-87.7%) lower among fully vaccinated persons without prior infection; and 82.4% (70.8%-89.3%) lower among persons fully vaccinated after prior infection. CONCLUSIONS: Two doses of Pfizer-BioNTech COVID-19 vaccine reduced SARS-CoV-2 infection risk by ≥80% and, for those with prior infection, increased protection from prior infection alone. These findings support recommendations that all eligible persons, regardless of prior infection, be vaccinated against COVID-19.


Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , BNT162 Vaccine , COVID-19 Testing , Long-Term Care , New York City/epidemiology , SARS-CoV-2 , Nursing Homes
4.
Clin Infect Dis ; 2022 May 20.
Article in English | MEDLINE | ID: covidwho-2232407

ABSTRACT

BACKGROUND: Belief that vaccination is not needed for individuals with prior infection contributes to COVID-19 vaccine hesitancy. Among individuals infected with SARS-CoV-2 before vaccines became available, we assessed whether vaccinated individuals had reduced odds of reinfection. METHODS: We conducted a case-control study among adult New York City residents who tested positive for SARS-CoV-2 infection in 2020, did not test positive again >90 days after initial positive test through July 1, 2021, and did not die before July 1, 2021. Case-patients with reinfection during July-November 2021 and control subjects with no reinfection were matched (1:3) on age, sex, timing of initial positive test in 2020, and neighborhood poverty level. Matched odds ratios (mOR) and 95% confidence intervals (CI) were calculated using conditional logistic regression. RESULTS: Of 349,827 eligible adults, 2,583 were reinfected during July-November 2021. Of 2,401 with complete matching criteria data, 1,102 (45.9%) were known to be symptomatic for COVID-19-like-illness, and 96 (4.0%) were hospitalized. Unvaccinated individuals, compared with individuals fully vaccinated within the prior 90 days, had elevated odds of reinfection (mOR, 3.21; 95% CI, 2.70, 3.82), of symptomatic reinfection (mOR, 2.97; 95% CI, 2.31, 3.83), and of reinfection with hospitalization (mOR, 2.09; 95% CI, 0.91, 4.79). All three vaccines authorized or approved for use in the U.S. were similarly effective. CONCLUSION: Vaccination reduced odds of reinfections when the Delta variant predominated. Further studies should assess risk of severe outcomes among reinfected persons as new variants emerge, infection- and vaccine-induced immunity wanes, and booster doses are administered.

5.
Influenza Other Respir Viruses ; 2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2230519

ABSTRACT

BACKGROUND: Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness. METHODS: We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases. RESULTS: Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87). CONCLUSIONS: Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.

7.
JMIR Public Health Surveill ; 7(1): e25538, 2021 01 15.
Article in English | MEDLINE | ID: covidwho-2141302

ABSTRACT

BACKGROUND: Nowcasting approaches enhance the utility of reportable disease data for trend monitoring by correcting for delays, but implementation details affect accuracy. OBJECTIVE: To support real-time COVID-19 situational awareness, the New York City Department of Health and Mental Hygiene used nowcasting to account for testing and reporting delays. We conducted an evaluation to determine which implementation details would yield the most accurate estimated case counts. METHODS: A time-correlated Bayesian approach called Nowcasting by Bayesian Smoothing (NobBS) was applied in real time to line lists of reportable disease surveillance data, accounting for the delay from diagnosis to reporting and the shape of the epidemic curve. We retrospectively evaluated nowcasting performance for confirmed case counts among residents diagnosed during the period from March to May 2020, a period when the median reporting delay was 2 days. RESULTS: Nowcasts with a 2-week moving window and a negative binomial distribution had lower mean absolute error, lower relative root mean square error, and higher 95% prediction interval coverage than nowcasts conducted with a 3-week moving window or with a Poisson distribution. Nowcasts conducted toward the end of the week outperformed nowcasts performed earlier in the week, given fewer patients diagnosed on weekends and lack of day-of-week adjustments. When estimating case counts for weekdays only, metrics were similar across days when the nowcasts were conducted, with Mondays having the lowest mean absolute error of 183 cases in the context of an average daily weekday case count of 2914. CONCLUSIONS: Nowcasting using NobBS can effectively support COVID-19 trend monitoring. Accounting for overdispersion, shortening the moving window, and suppressing diagnoses on weekends-when fewer patients submitted specimens for testing-improved the accuracy of estimated case counts. Nowcasting ensured that recent decreases in observed case counts were not overinterpreted as true declines and supported officials in anticipating the magnitude and timing of hospitalizations and deaths and allocating resources geographically.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance/methods , Bayes Theorem , Humans , New York City/epidemiology , Retrospective Studies
8.
MMWR Morb Mortal Wkly Rep ; 69(46): 1725-1729, 2020 11 20.
Article in English | MEDLINE | ID: covidwho-1876240

ABSTRACT

New York City (NYC) was an epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States during spring 2020 (1). During March-May 2020, approximately 203,000 laboratory-confirmed COVID-19 cases were reported to the NYC Department of Health and Mental Hygiene (DOHMH). To obtain more complete data, DOHMH used supplementary information sources and relied on direct data importation and matching of patient identifiers for data on hospitalization status, the occurrence of death, race/ethnicity, and presence of underlying medical conditions. The highest rates of cases, hospitalizations, and deaths were concentrated in communities of color, high-poverty areas, and among persons aged ≥75 years or with underlying conditions. The crude fatality rate was 9.2% overall and 32.1% among hospitalized patients. Using these data to prevent additional infections among NYC residents during subsequent waves of the pandemic, particularly among those at highest risk for hospitalization and death, is critical. Mitigating COVID-19 transmission among vulnerable groups at high risk for hospitalization and death is an urgent priority. Similar to NYC, other jurisdictions might find the use of supplementary information sources valuable in their efforts to prevent COVID-19 infections.


Subject(s)
Coronavirus Infections/epidemiology , Disease Outbreaks , Pneumonia, Viral/epidemiology , Adolescent , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Female , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , New York City/epidemiology , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , SARS-CoV-2 , Young Adult
9.
Vaccine X ; 10: 100134, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1587103

ABSTRACT

BACKGROUND: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. METHODS: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. RESULTS: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). CONCLUSION: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

10.
Clin Infect Dis ; 73(9): 1707-1710, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1501054

ABSTRACT

Using a population-based, representative telephone survey, ~930 000 New York City residents had COVID-19 illness beginning 20 March-30 April 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics.


Subject(s)
COVID-19 , Hospitalization , Humans , New York City/epidemiology , SARS-CoV-2
12.
MMWR Morb Mortal Wkly Rep ; 69(28): 918-922, 2020 Jul 17.
Article in English | MEDLINE | ID: covidwho-1389847

ABSTRACT

To limit introduction of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), the United States restricted travel from China on February 2, 2020, and from Europe on March 13. To determine whether local transmission of SARS-CoV-2 could be detected, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) conducted deidentified sentinel surveillance at six NYC hospital emergency departments (EDs) during March 1-20. On March 8, while testing availability for SARS-CoV-2 was still limited, DOHMH announced sustained community transmission of SARS-CoV-2 (1). At this time, twenty-six NYC residents had confirmed COVID-19, and ED visits for influenza-like illness* increased, despite decreased influenza virus circulation.† The following week, on March 15, when only seven of the 56 (13%) patients with known exposure histories had exposure outside of NYC, the level of community SARS-CoV-2 transmission status was elevated from sustained community transmission to widespread community transmission (2). Through sentinel surveillance during March 1-20, DOHMH collected 544 specimens from patients with influenza-like symptoms (ILS)§ who had negative test results for influenza and, in some instances, other respiratory pathogens.¶ All 544 specimens were tested for SARS-CoV-2 at CDC; 36 (6.6%) tested positive. Using genetic sequencing, CDC determined that the sequences of most SARS-CoV-2-positive specimens resembled those circulating in Europe, suggesting probable introductions of SARS-CoV-2 from Europe, from other U.S. locations, and local introductions from within New York. These findings demonstrate that partnering with health care facilities and developing the systems needed for rapid implementation of sentinel surveillance, coupled with capacity for genetic sequencing before an outbreak, can help inform timely containment and mitigation strategies.


Subject(s)
Betacoronavirus/genetics , Betacoronavirus/isolation & purification , Community-Acquired Infections/diagnosis , Community-Acquired Infections/virology , Coronavirus Infections/diagnosis , Coronavirus Infections/virology , Pneumonia, Viral/diagnosis , Pneumonia, Viral/virology , Sentinel Surveillance , Adolescent , Adult , Aged , COVID-19 , Child , Child, Preschool , Community-Acquired Infections/epidemiology , Coronavirus Infections/epidemiology , Emergency Service, Hospital , Female , Humans , Infant , Male , Middle Aged , New York City/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Sequence Analysis , Travel-Related Illness , Young Adult
13.
Ann Epidemiol ; 63: 46-51, 2021 11.
Article in English | MEDLINE | ID: covidwho-1351545

ABSTRACT

PURPOSE: To examine neighborhood-level disparities in SARS-CoV-2 molecular test percent positivity in New York City (NYC) by demographics and socioeconomic status over time to better understand COVID-19 inequities. METHODS: Across 177 neighborhoods, we calculated the Spearman correlation of neighborhood characteristics with SARS-CoV-2 molecular test percent positivity during March 1-July 25, 2020 by five periods defined by trend in case counts: increasing, declining, and three plateau periods to account for differential testing capacity and reopening status. RESULTS: Percent positivity was positively correlated with neighborhood racial and ethnic characteristics and socioeconomic status, including the proportion of the population who were Latino and Black non-Latino, uninsured, Medicaid enrollees, transportation workers, or had low educational attainment. Correlations were generally consistent over time despite increasing testing rates. Neighborhoods with high proportions of these correlates had median percent positivity values of 62.6%, 28.7%, 6.4%, 2.8%, and 2.2% in the five periods, respectively, compared with 40.6%, 11.7%, 1.7%, 0.9%, and 1.0% in neighborhoods with low proportions of these correlates. CONCLUSIONS: Disparities in SARS-CoV-2 molecular test percent positivity persisted in disadvantaged neighborhoods during multiple phases of the first few months of the COVID-19 epidemic in NYC. Mitigation of the COVID-19 burden is still urgently needed in disproportionately affected communities.


Subject(s)
COVID-19 , SARS-CoV-2 , Hispanic or Latino , Humans , New York City/epidemiology , Residence Characteristics , Socioeconomic Factors
14.
J Racial Ethn Health Disparities ; 9(4): 1584-1599, 2022 08.
Article in English | MEDLINE | ID: covidwho-1349374

ABSTRACT

BACKGROUND: COVID-19 mortality studies have primarily focused on persons aged ≥ 65 years; less is known about decedents aged <65 years. METHODS: We conducted a case-control study among NYC residents aged 21-64 years hospitalized with COVID-19 diagnosed March 13-April 9, 2020, to determine risk factors for death. Case-patients (n=343) were hospitalized decedents with COVID-19 and control-patients (n=686) were discharged from hospitalization with COVID-19 and matched 2:1 to case-patients on age and residential neighborhood. Conditional logistic regression models were adjusted for patient sex, insurance status, and marital status. Matched adjusted odds ratios (aORs) were calculated for selected underlying conditions, combinations of conditions, and race/ethnic group. RESULTS: Median age of both case-patients and control-patients was 56 years (range: 23-64 years). Having ≥ 1 selected underlying condition increased odds of death 4.45-fold (95% CI: 2.33-8.49). Patients with diabetes; morbid obesity; heart, kidney, or lung disease; cancer; neurologic/neurodevelopmental conditions; mental health conditions; or HIV had significantly increased odds of death. Compared with having neither condition, having both diabetes and obesity or diabetes and heart disease was associated with approximately threefold odds of death. Five select underlying conditions were more prevalent among non-Hispanic Black control-patients than among control-patients of other races/ethnicities. CONCLUSIONS AND RELEVANCE: Selected underlying conditions were risk factors for death, and most prevalent among racial/ethnic minorities. Social services; health care resources, including vaccination; and tailored public health messaging are important for COVID-19 prevention. Strengthening these strategies for racial/ethnic minority groups could minimize COVID-19 racial/ethnic disparities.


Subject(s)
COVID-19 , Adult , Case-Control Studies , Ethnicity , Humans , Middle Aged , Minority Groups , New York City/epidemiology , Risk Factors , SARS-CoV-2 , Young Adult
15.
Emerg Infect Dis ; 27(5)2021 05.
Article in English | MEDLINE | ID: covidwho-1201388

ABSTRACT

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.


Subject(s)
COVID-19 , Humans , New York City/epidemiology , Prospective Studies , SARS-CoV-2
16.
Lancet Infect Dis ; 21(2): 203-212, 2021 02.
Article in English | MEDLINE | ID: covidwho-1137671

ABSTRACT

BACKGROUND: As the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear. METHODS: In this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening). FINDINGS: During the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older. INTERPRETATION: Our results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds. FUNDING: National Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.


Subject(s)
COVID-19/mortality , Pandemics , SARS-CoV-2 , Adolescent , Adult , Aged , Algorithms , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Male , Middle Aged , Models, Theoretical , Mortality , New York City/epidemiology , Public Health Surveillance , Young Adult
17.
medRxiv ; 2020 Oct 20.
Article in English | MEDLINE | ID: covidwho-900762

ABSTRACT

To account for delays between specimen collection and report, the New York City Department of Health and Mental Hygiene used a time-correlated Bayesian nowcasting approach to support real-time COVID-19 situational awareness. We retrospectively evaluated nowcasting performance for case counts among residents diagnosed during March-May 2020, a period when the median reporting delay was 2 days. Nowcasts with a 2-week moving window and a negative binomial distribution had lower mean absolute error, lower relative root mean square error, and higher 95% prediction interval coverage than nowcasts conducted with a 3-week moving window or with a Poisson distribution. Nowcasts conducted toward the end of the week outperformed nowcasts performed earlier in the week, given fewer patients diagnosed on weekends and lack of day-of-week adjustments. When estimating case counts for weekdays only, metrics were similar across days the nowcasts were conducted, with Mondays having the lowest mean absolute error, of 183 cases in the context of an average daily weekday case count of 2,914. Nowcasting ensured that recent decreases in observed case counts were not overinterpreted as true declines and supported health department leadership in anticipating the magnitude and timing of hospitalizations and deaths and allocating resources geographically.

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