Periodic Oscillations in Daily Reported Infections and Deaths for Coronavirus Disease 2019

Bukhari, Qasim; Jameel, Yusuf; Massaro, Joseph M.; D’Agostino, Ralph B.; Khan, Sheraz

doi:10.1001/jamanetworkopen.2020.17521

Cited by 24 publications

(25 citation statements)

References 4 publications

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“…10 2.7-7.6 GC/g ( Cheung et al 2020 , Pan et al 2020 )) and the rapid changing of fecal viral load in individual patients over the disease course ( Jones et al 2020 , Wolfel et al 2020 ) can generate different fluxes of total SARS-CoV-2 RNA mass in the sewer systems. Significant daily fluctuation of new clinical cases in Honolulu was also observed ( Figure 1 ), which was similar to weekly inter-day oscillations widely observed in other communities experiencing COVID-19 disease outbreaks ( Bukhari et al 2020 ). Although this phenomenon has been considered by many to be primarily a reflection of diagnostic and reporting biases ( Bergman et al 2020 ), contribution from fluctuations in disease burden remains as a possibility ( Ricon-Becker et al 2020 ), as individual communities can experience different disease transmission dynamics.…”

Section: Discussionsupporting

confidence: 80%

Fine-Scale Temporal Dynamics of SARS-CoV-2 RNA Abundance in Wastewater during A COVID-19 Lockdown

Saingam

et al. 2021

Water Research

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Wastewater is a pooled sampling instrument that may provide rapid and even early disease signals in the surveillance of COVID-19 disease at the community level, yet the fine-scale temporal dynamics of SARS-CoV-2 RNA in wastewater remains poorly understood. This study tracked the daily dynamics of SARS-CoV-2 RNA in the wastewater from two wastewater treatment plants (WWTPs) in Honolulu during a rapidly expanding COVID-19 outbreak and a responding four-week lockdown that resulted in a rapid decrease of daily clinical COVID-19 new cases. The wastewater SARS-CoV-2 RNA concentration from both WWTPs, as measured by three quantification assays (N1, N2, and E), exhibited both significant inter-day fluctuations (10 1.2 -10 5.1 gene copies or GC/L in wastewater liquid fractions, or 10 1.4 -10 6.2 GC/g in solid fractions) and an overall downward trend over the lockdown period. Strong and significant correlation was observed in measured SARS-CoV-2 RNA concentrations between the solid and liquid wastewater fractions, with the solid fraction containing majority (82.5%-92.5%) of the SARS-CoV-2 RNA mass and the solid-liquid SARS-CoV-2 RNA concentration ratios ranging from 10 3.6 to 10 4.3 mL/g. The measured wastewater SARS-CoV-2 RNA concentration was normalized by three endogenous fecal RNA viruses (F + RNA coliphages Group II and III, and pepper mild mottle virus) to account for potential variations that may occur during the multi-step wastewater processing and molecular quantification, and the normalized abundance also exhibited similar daily fluctuations and overall downward trend.

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Section: Discussionsupporting

confidence: 80%

Fine-Scale Temporal Dynamics of SARS-CoV-2 RNA Abundance in Wastewater during A COVID-19 Lockdown

Saingam

et al. 2021

Water Research

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“…Outcomes were aggregated by week in order to control for daily patterns evident in Canadian case reporting data. 16 The Open Data Working Group obtains and compiles daily case counts reported across the country by provincial public health agencies, accredited news media and oficial social media accounts. Weeks were defined as starting on Sunday and ending on Saturday.…”

Section: Outcomementioning

confidence: 99%

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada

Brown

Soucy

Buchan

et al. 2021

CMAJ

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BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the diference relative to the observed mobility level (i.e., mobility gap). METHODS:We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of Early release, published at www.cmaj.ca on April 7, 2021. Subject to revision.

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“…We measured the weekly case counts and test positivity in each province using data from COVID-19 Canada Open Data Working Group (12), in the 44-week period from March 15, 2020 to January 16, 2021. Outcomes were aggregated by week in order to control for day-of-the-week patterns evident in Canadian case reporting data (13). The Open Data Working Group obtains and compiles daily case counts reported across the country by provincial public health agencies, accredited news media, and official social media accounts.…”

Section: Methodsmentioning

confidence: 99%

The mobility gap: estimating mobility levels required to control Canada’s winter COVID-19 surge

Brown

Soucy

et al. 2021

Preprint

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BackgroundNon-pharmaceutical interventions remain a primary means of suppressing COVID-19 until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures in seven Canadian provinces to quantify the mobility level needed to suppress COVID-19 (mobility threshold), and the difference relative to current mobility levels (mobility gap).MethodsWe conducted a longitudinal study of weekly COVID-19 incidence from March 15, 2020 to January 16, 2021, among provinces with 20 COVID-19 cases in at least 10 weeks. The outcome was weekly growth rate defined as the ratio of current cases compared to the previous week. We examined the effects of average time spent outside the home (non-residential mobility) in the prior three weeks using a lognormal regression model accounting for province, season, and mean temperature. We calculated the COVID-19 mobility threshold and gap.ResultsAcross the 44-week study period, a total of 704,294 persons were infected with COVID-19. Non-residential mobility dropped rapidly in the spring and reached a median of 36% (IQR: 31,40) in April 2020. After adjustment, each 5% increase in non-residential mobility was associated with a 9% increase in the COVID-19 weekly growth rate (ratio=1.09, 95%CI: 1.07,1.12). The mobility gap increased through the fall months, which was associated with increasing case growth.InterpretationMobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control COVID-19 through winter 2021. Mobility measures from anonymized smartphone data can be used to guide the provincial and regional implementation and loosening of physical distancing measures.

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Periodic Oscillations in Daily Reported Infections and Deaths for Coronavirus Disease 2019

Cited by 24 publications

References 4 publications

Fine-Scale Temporal Dynamics of SARS-CoV-2 RNA Abundance in Wastewater during A COVID-19 Lockdown

Fine-Scale Temporal Dynamics of SARS-CoV-2 RNA Abundance in Wastewater during A COVID-19 Lockdown

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada

The mobility gap: estimating mobility levels required to control Canada’s winter COVID-19 surge

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