Spatially refined time-varying reproduction numbers of SARS-CoV-2 in Arkansas and Kentucky and their relationship to population size and public health policy, March – November 2020

Politis, Maria D.; Hua, Xinyi; Ogwara, Chigozie A.; Davies, Margaret R.; Adebile, Temitayo M.; Sherman, Maya P.; Zhou, Xiaolu; Chowell, Gerardo; Spaulding, Anne C.; Fung, Isaac Chun-Hai

doi:10.1016/j.annepidem.2021.12.012

Cited by 9 publications

(6 citation statements)

References 34 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…40 Politis et al found facemask mandate was associated with a decrease in R t by 11% and 6%, respectively, in Arkansas and Kentucky. 10 Thus, our findings in South Carolina are consistent with findings in other states that a mask mandate was associated with slowing epidemic growth.…”

Section: Discussionsupporting

confidence: 90%

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 – January 2021

Davies

Hua

Jacobs

et al. 2022

Disaster med. public health prep.

Self Cite

View full text Add to dashboard Cite

Introduction: We aimed to examine how public health policies influenced the dynamics of COVID-19 time-varying reproductive number (R t ) in South Carolina from February 26, 2020 to January 1, 2021. Methods: COVID-19 case series (March 6, 2020 - January 10, 2021) were shifted by 9 days to approximate the infection date. We analyzed the effects of state and county policies on R t using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size. Results: R t shifted from 2-3 in March to <1 during April and May. R t rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in R t (-15.3%; 95% CrI, -13.6%, -16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rate (p<0.0001). Conclusion: The R t dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing non-essential businesses, were associated with R t reduction, while policies that encouraged more movement, such as re-opening schools, were associated with R t increase.

show abstract

Section: Discussionsupporting

confidence: 90%

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 – January 2021

Davies

Hua

Jacobs

et al. 2022

Disaster med. public health prep.

Self Cite

View full text Add to dashboard Cite

show abstract

“…We performed R e estimation analysis using the "EpiEstim" package [94]. Researchers have widely used this package to determine the epidemic trajectory in different settings [34,91,95].…”

Section: Epidemic Trajectory Analysismentioning

confidence: 99%

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

2023

View full text Add to dashboard Cite

Introduction: Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown’s impact on COVID-19 cases and associated healthcare costs. Methods: Using daily case data for 84 days (9 March–31 May 2020), we modeled the epidemic’s trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R0), daily reproduction number (Re), and case doubling time. Based on pre-restriction and Phase 1 R0, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis. Results: The estimated median R0 during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, −15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, –204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83). Conclusion: Maharashtra’s early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.

show abstract

mentioning

confidence: 99%

“…This should not be unexpected since Iran is the epicentre of the pandemic in the Middle East. In the United States,Politis et al (2022) investigated the timevarying reproduction number in Arkansas and Kentucky, reporting peak values of 1.15 and 1.10, respectively.CONCLUSSIONIt is apparent that COVID-19 pandemic has passed, especially with the recent declaration by WHO Director-General (WHO, 2023) that COVID-19 is no longer a public health emergency of international concern, and the follow-up statement issued by the NCDC (NCDC, 2023). However, with international travelling restrictions lifted and COVID-19 protocols relaxed, both WHO and the NCDC cautioned that the dangers posed by the virus still remains within communities and hence a significant risk of transmitting a strain or new variants across the globe.…”

mentioning

confidence: 99%

“…These lower values were achieved through policies and measures that effectively slowed transmission of the pandemic(Politis et al, 2022) From pandemic onset, age and gender have been identified as significant risk factors(Goldstein et al, 2021;Permata et al, 2021;Hu et al, 2021) in the dynamics of COVID-19 transmission. A study of the third wave of the pandemic in New York City byTandon et al (2022) revealed that males were the most affected, with mean age of 60±19 years at infection.…”

mentioning

confidence: 99%

See 1 more Smart Citation

An Estimate of Time-Dependent Transmission of COVID-19 Pandemic in Katsina State from June to November 2021

Rabe,

Idris

2022

USci

View full text Add to dashboard Cite

This paper investigates the spread of COVID-19 pandemic in Katsina state from 23rd June to 27th November, 2021, using graphical tools to visually analyse infection over time and time-dependent reproduction number to quantify the transmissibility of the disease. Study data consist of diagnostic results of reverse transcriptase real-time quantitative polymerase chain reaction assays (RT-PCR) on nine hundred and eighty-nine nasal swab samples from suspected COVID-19 cases, collected from public and private health facilities across Local government areas of the State and analysed by the Molecular Laboratory of the Federal Medical Centre Katsina, recording a total of 137 positive cases. Our investigation revealed that, over the study period, COVID-19 transmission reaches its peak on 17th October 2021 (Epidemic Week 41), with a mean Reproduction number (Rt) of 3.22 and a standard deviation of 0.5976 (95% CI: 2.6193 - 3.8145), culminating in 19 new infections on Wednesday the 27th (Epidemic Week 43). The combined age groups 21-30 and 31-40 constituted the most affected cases with 29 (21.17%) and 19 (13.87%) positive cases, respectively. This was closely followed by age group 51-60 with 19 (13.87%) positive cases. On gender basis, 70 (51%) females tested positive compared to 67 (49%) males. We therefore conclude that for the third wave of COVID-19 pandemic in Katsina State, disease transmission reaches its peak in Epidemic Week 41 in October, then rapidly diminishes to Rt values of less than one, indicating that no new infections were expected by the end of November, with female gender and age groups in the range 21 to 40 years being most infected. We recommend that mitigation strategies that take into consideration features inherent in female gender and more pronounced in young (21 to 40 years) and middle-aged (51-60 years) adults should be adopted in case of future waves.

show abstract

Spatially refined time-varying reproduction numbers of SARS-CoV-2 in Arkansas and Kentucky and their relationship to population size and public health policy, March – November 2020

Cited by 9 publications

References 34 publications

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 – January 2021

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 – January 2021

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

An Estimate of Time-Dependent Transmission of COVID-19 Pandemic in Katsina State from June to November 2021

Contact Info

Product

Resources

About