Estimation of R(t) based on illness onset data: An analysis of 1907–1908 smallpox epidemic in Tokyo

Nakajo, Ko; Nishiura, Hiroshi

doi:10.1016/j.epidem.2022.100545

Cited by 4 publications

(6 citation statements)

References 27 publications

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“…We used methods proposed by Nakajo and Nishiura for calculating R t ( 53 , 54 ). The R t of COVID-19 was estimated as the epidemiological outcome, particularly its absolute and relative changes before and after the start of interventions.…”

Section: Methodsmentioning

confidence: 99%

“…Following Nakajo and Nishiura ( 53 , 54 ) we assumed that x is the duration of infectiousness prior to illness onset, and we set x = 5 days (i.e., cases became infectious 5 days prior to the illness onset date). f s was assumed to follow a lognormal distribution with mean 5.2 days and variance 14.9 ( 55 ), and λ u was assumed to follow a gamma distribution with mean 12.9 days and variance 8.1 ( 56 ).…”

Section: Methodsmentioning

confidence: 99%

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Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021

et al. 2022

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BackgroundPublic health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility.Materials and MethodsWe investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (Rt) before and after these interventions, and then analyzed the relationship between lower Rt values and each PHSM.ResultsWith implementation of pre-emergency measures (PEM) in 16 prefectures, the Rt was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated Rt < 1, and the average relative reduction was 26%–39%. No single intervention was identified that uniquely resulted in an Rt value < 1.ConclusionAn SoE can substantially reduce the Rt and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the Rt value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021

et al. 2022

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“…We estimated R t using date of symptom onset and date of infection (13,31). When R t was classified by date of symptom onset, the expected case count on day t was proportional to R t and a convolution of case counts on previous days with the serial interval distribution.…”

Section: Estimating Epidemiologic Parametersmentioning

confidence: 99%

“…When R t was classified by date of symptom onset, the expected case count on day t was proportional to R t and a convolution of case counts on previous days with the serial interval distribution. When R t was classified by date of infection, the formula had a more complicated form and contained a double convolution, involving the incubation period and profile of infectiousness (31,32) (Appendix). Because some case records did not contain information on symptom onset date, we back-projected those cases from the date the case was confirmed to a presumptive date of symptom onset, using a timevaried distribution of the reporting delay.…”

Section: Estimating Epidemiologic Parametersmentioning

confidence: 99%

Transmission Dynamics and Effectiveness of Control Measures during COVID-19 Surge, Taiwan, April–August 2021

Akhmetzhanov¹,

Cheng²,

Linton³

et al. 2022

Emerg. Infect. Dis.

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began infecting humans in Wuhan, China, in December 2019. Within 1 year, SARS-CoV-2 spread to nearly all countries, and >178 million infections and 3.7 million deaths were reported by April 2021. Taiwan, an island with 23.8 million inhabitants, reported only slightly more than 1,000 cases by April 2021, despite being located close to the original epicenter of the COVID-19 outbreak. At that time, most infections confirmed in Taiwan were acquired abroad, and <10% were acquired locally.The subsequent emergence of more transmissible SARS-CoV-2 variants led to multiple introductions from those traveling to and from Taiwan, initiating cryptic transmissions in the capital city of Taipei and its surroundings in April 2021. Newly detected clusters of the virus led to an explosive growth in cases, and daily reported case numbers reached 200 by mid-May. The sudden increase in cases prompted the government to implement stricter control measures to prevent disease spread, and those measures proved effective in bringing the epidemic under control by the end of July. Those preventive measures included restricting public movement, enforcing compulsory shortening of business hours, implementing workfrom-home for nonessential businesses, banning inrestaurant dining, and canceling social and religious gatherings. By October 2021, Taiwan was again reporting 0 cases daily.The initial clusters of infections in 2021 were linked to international pilots and flight crew members, but the major epidemic hotspots were identified as owners and visitors of tea houses, which are landmarks in some districts of Taipei. Although tea houses in Taipei typically offer tea and other refreshments during the day, some also conduct business in the evening, when the potential for activities that increase risk for the transmission of SARS-CoV-2 (e.g., close physical contact) is greater and timely detection of infections can be hindered (1-3). In nightlife districts across the city, patrons and staff of tea houses and other establishments often are unwilling to share contact and travel histories with public health officials. Outside of Taipei and New Taipei City, clusters of infections were frequently linked to factories or other production sites, affecting vulnerable social groups such as migrant workers. Some initial clusters were linked to local markets and initiated by vendors traveling to the Taipei area for commercial purposes.

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“…Thus, for ongoing epidemics, the appropriate methodology would be the estimation of the time-varying reproduction number ( R t ), which is defined as the average number of secondary cases per primary case at a given time t (Cori et al, 2013; Merl et al, 2009; Vegvari et al, 2021). To reduce distortions on the epidemic curve in outbreaks where the case counting is obtained by the date of notification the use of models that accounts for uncertainty, associated with delays between symptoms onset and the date of notification, would be an appropriate approach (Abbott et al, 2020; Gostic et al, 2020; Nakajo & Nishiura, 2022; Probert et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Assessing epidemiological parameters and dissemination characteristics of the 2000 and 2001 foot-and-mouth disease outbreaks in Rio Grande do Sul, Brazil

Costa

Cobellini

Cárdenas

et al. 2022

Preprint

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Since 1998 the state of Rio Grande do Sul, Brazil, has been free of foot-and-mouth disease (FMD) with yearly mandatory vaccination, until the 2000 and 2001 reintroductions. This study gathers data from both outbreaks including official veterinary state service archives and field investigation reports to quantify epidemiological parameters such as epidemic duration, number of secondary infected farms and animals, and estimate the epidemic rate of growth. We apply a Bayesian latent variable approach to estimate the time-varying reproduction number and calculate new confirmed cases by infection date. Additionally, we utilized between-farm animal movements to reconstruct possible FMD transmission and characteristics of spread over the current at-risk population, by incorporating bovine movement data from 2018 to 2020 as standard to benchmark infected network parameters. The results were consistent with the reports generated by the official investigation of the outbreaks and the models and results presented in this study may be useful for assessing the transmission dynamics and support control measures in the future.

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Estimation of R(t) based on illness onset data: An analysis of 1907–1908 smallpox epidemic in Tokyo

Cited by 4 publications

References 27 publications

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021

Transmission Dynamics and Effectiveness of Control Measures during COVID-19 Surge, Taiwan, April–August 2021

Assessing epidemiological parameters and dissemination characteristics of the 2000 and 2001 foot-and-mouth disease outbreaks in Rio Grande do Sul, Brazil

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