Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China

Wang, Junjun; Ma, Tao; Ding, Songning; Xu, Ke; Zhang, Min; Zhang, Zhong; Dai, Qi; Tao, Shilong; Wang, Hengxue; Cheng, Xiaoqing; He, Ming; Du, Xinying; Feng, Zhi; Yang, Huafeng; Wang, Rong; Xie, Chao-Yong; Xu, Yuanyuan; Liu, Li; Chen, Xupeng; Li, Chen; Wu, Wen Chih; Ye, Sheng; Yang, Shiwen; Fan, Huafeng; Zhou, Nan; Ding, Jie

doi:10.3389/fpubh.2022.933075

Cited by 7 publications

(8 citation statements)

References 32 publications

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“…Thirty-one studies [ 29 – 59 ] were included in this review (Table S 1 ). Studies included 17 research articles [ 29 , 32 , 34 , 35 , 40 , 42 , 43 , 45 – 48 , 50 , 53 – 55 , 57 , 59 ], eight brief communications [ 30 , 31 , 33 , 36 , 39 , 51 , 52 , 58 ], three letters [ 37 , 38 , 41 ], and three reports [ 44 , 49 , 56 ]. Studies were from Belgium [ 33 ], Brazil [ 37 ], China [ 34 – 36 , 42 , 44 , 45 , 49 – 51 , 53 – 57 , 59 ], Germany [ 29 ], Japan [ 46 ], Netherlands [ 30 ], Singapore [ 38 , 52 ], South Korea [ 32 , 39 – 41 , 58 ], Spain [ 31 ], U.K. [ 47 ], and U.S.A. [ 43 , 48 ].…”

Section: Resultsmentioning

confidence: 99%

“…Distributions used to fit the serial interval data were gamma (15 studies [ 29 , 36 , 44 – 47 , 52 – 59 ]), normal (five studies [ 32 – 34 , 39 , 40 ]), Weibull (three studies [ 42 , 49 , 50 ]), Gaussian (one study [ 37 ]), and skewed normal (one study [ 38 ]); the distribution was unspecified for four studies [ 30 , 31 , 35 , 41 ]. All studies but four reported mean and SD for serial interval.…”

Section: Resultsmentioning

confidence: 99%

“…Only two studies [ 47 , 57 ] reported mean generation time and two studies [ 51 , 54 ] reported adjusting for right truncation. Nine studies [ 29 , 30 , 38 , 41 , 42 , 47 , 48 , 50 , 58 ] were exclusively from the household setting. The study with the largest sample size [ 29 ] only reported the number of households included in the serial interval analysis rather than the number of primary/secondary case pairs.…”

Section: Resultsmentioning

confidence: 99%

“…Mean serial interval for included studies ranged from 2.3 days [ 44 ] to 5.8 days [ 31 , 54 ] for Delta and 2.1 days [ 43 , 59 ] to 4.8 days [ 31 ] for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4–4.3) (20 studies [ 29 – 31 , 33 – 35 , 37 – 39 , 42 – 49 , 52 – 54 ]) and Omicron was 3.2 days (95% CI: 2.9–3.5) (20 studies [ 29 – 33 , 36 , 40 , 41 , 43 , 48 , 50 – 59 ]) (Fig. 2 ).…”

Section: Resultsmentioning

confidence: 99%

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Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

et al. 2023

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Background The serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9–5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87–5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants. Methods This study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: (“serial interval” or “generation time”), (“Omicron” or “Delta”), and (“SARS-CoV-2” or “COVID-19”). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported. Results There were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3–5.8 days for Delta and 2.1–4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4–4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9–3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8–3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7–3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6–3.1) (three studies). Conclusions Serial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

et al. 2023

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“…The SARS-CoV-2 Omicron variant spread rapidly nationwide since November 2022, seriously affecting the health of residents. In previous studies, the factors associated with the infection rate of COVID-19 might include socio-demographic factors such as gender, age, and occupation, but the results were not entirely consistent ( 8 , 9 ), whereas vaccination has presented a certain protective effect against COVID-19 ( 10 , 11 ). And in the few studies of reinfection in China, the factors influencing reinfection rates were similar to those of initial infection ( 12 , 13 ).…”

Section: Introductionmentioning

confidence: 86%

Epidemiological and clinical characteristics of COVID-19 reinfection during the epidemic period in Yangzhou city, Jiangsu province

Wang,

Liang,

Yang

et al. 2023

Front. Public Health

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BackgroundWith the continuous progress of the epidemic of coronavirus disease 2019 (COVID-19) infection and the constant mutation of the virus strain, reinfection occurred in previously infected individuals and caused waves of the epidemic in many countries. Therefore, we aimed to explore the characteristics of COVID-19 reinfection during the epidemic period in Yangzhou and provide a scientific basis for assessing the COVID-19 situation and optimizing the allocation of medical resources.MethodsWe chose previously infected individuals of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reported locally in Yangzhou city from January 2020 to November 30, 2022. A telephone follow-up of cases was conducted from February to March 2023 to collect the COVID-19 reinfection information. We conducted a face-to-face survey on that who met the definition of reinfection to collect information on clinical symptoms, vaccination status of COVID-19, and so on. Data were analyzed using SPSS 19.0.ResultsAmong the 999 eligible respondents (92.24% of all the participants), consisting of 42.28% males and 57.72% females, the reinfection incidence of females was significantly higher than that of male cases (χ2 = 5.197, P < 0.05); the ages of the respondents ranged from 1 to 91 years, with the mean age of 42.28 (standard deviation 22.73) years; the most of the sufferers were infected initially with Delta variant (56.88%), followed by the Omicron subvariants BA.1/BA.2 (39.52%). Among all the eligible respondents, 126 (12.61%) reported COVID-19 reinfection appearing during the epidemic period, and the intervals between infections were from 73 to 1,082 days. The earlier the initial infection occurred, the higher the reinfection incidence and the reinfection incidence was significantly increased when the interval was beyond 1 year (P < 0.01) .119 reinfection cases (94.4%) were symptomatic when the most common symptoms included fever (65.54%) and cough (61.34%); compared with the initial infection cases, the proportion of clinical symptoms in the reinfected cases was significantly higher (P < 0.01). The reinfection incidence of COVID-19 vaccination groups with different doses was statistically significant (P < 0.01). Fewer reinfections were observed among the respondents with three doses of COVID-19 vaccination compared to the respondents with two doses (χ2 = 14.595, P < 0.001) or without COVID-19 vaccination (χ2 =4.263, P = 0.039).ConclusionAfter the epidemic period of COVID-19, the reinfection incidence varied with different types of SARS-CoV-2 strains. The reinfection incidence was influenced by various factors such as virus characteristics, vaccination, epidemic prevention policies, and individual variations. As the SARS-CoV-2 continues to mutate, vaccination and appropriate personal protection have practical significance in reducing the risk of reinfection.

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Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis

Kummer

Zhao

et al. 2023

Preprint

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Background: After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern. Methods: We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2. Results: Our study included 274 records obtained from 147 household studies, contact tracing studies or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods. Specifically, we found that Omicron had the shortest pooled estimates for the incubation period (3.63 days, 95%CI: 3.25-4.02 days), serial interval (3.19 days, 95%CI: 2.95-3.43 days), and realized generation time (2.96 days, 95%CI: 2.54-3.38 days) whereas the ancestral lineage had the highest pooled estimates for each of them. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. We found considerable heterogeneities (I2 > 80%) when pooling the estimates across different virus lineages, indicating potential unmeasured confounding from population factors (e.g., social behavior, deployed interventions). Conclusion: Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves. Keywords: COVID-19, variants of concern, incubation period, serial interval, realized generation time, intrinsic generation time, systematic review, meta-analysis

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Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China

Cited by 7 publications

References 32 publications

Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

Rapid review and meta-analysis of serial intervals for SARS-CoV-2 Delta and Omicron variants

Epidemiological and clinical characteristics of COVID-19 reinfection during the epidemic period in Yangzhou city, Jiangsu province

Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis

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