ABSTRACT
The two nearby Amazonian cities of Iquitos and Manaus endured explosive COVID-19 epidemics and may well have suffered the world's highest infection and death rates over 2020, the first year of the pandemic. State-of-the-art epidemiological and modeling studies estimated that the populations of both cities came close to attaining herd immunity (>70% infected) at the termination of the first wave and were thus protected. This makes it difficult to explain the more deadly second wave of COVID-19 that struck again in Manaus just months later, simultaneous with the appearance of a new P.1 variant of concern, creating a catastrophe for the unprepared population. It was suggested that the second wave was driven by reinfections, but the episode has become controversial and an enigma in the history of the pandemic. We present a data-driven model of epidemic dynamics in Iquitos, which we also use to explain and model events in Manaus. By reverse engineering the multiple epidemic waves over 2 y in these two cities, the partially observed Markov process model inferred that the first wave left Manaus with a highly susceptible and vulnerable population (≈40% infected) open to invasion by P.1, in contrast to Iquitos (≈72% infected). The model reconstructed the full epidemic outbreak dynamics from mortality data by fitting a flexible time-varying reproductive number [Formula: see text] while estimating reinfection and impulsive immune evasion. The approach is currently highly relevant given the lack of tools available to assess these factors as new SARS-CoV-2 virus variants appear with different degrees of immune evasion.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2/genetics , Cities/epidemiology , PandemicsABSTRACT
There has long been controversy over the potential for asymptomatic cases of the influenza virus to have the capacity for onward transmission, but recognition of asymptomatic transmission of COVID-19 stimulates further research into this topic. Here, we develop a Bayesian methodology to analyze detailed data from a large cohort of 727 households and 2515 individuals in the 2009 pandemic influenza A(H1N1) outbreak in Hong Kong to characterize household transmission dynamics and to estimate the relative infectiousness of asymptomatic versus symptomatic influenza cases. The posterior probability that asymptomatic cases [36% of cases; 95% credible interval (CrI): 32%, 40%] are less infectious than symptomatic cases is 0.82, with estimated relative infectiousness 0.57 (95% CrI: 0.11, 1.54). More data are required to strengthen our understanding of the contribution of asymptomatic cases to the spread of influenza.
Subject(s)
COVID-19 , Influenza A Virus, H1N1 Subtype , Influenza, Human , Humans , Bayes Theorem , COVID-19/epidemiology , Disease OutbreaksABSTRACT
Like other tropical and subtropical regions, influenza viruses can circulate year-round in Hong Kong. However, during the COVID-19 pandemic, there was a significant decrease in influenza activity. The objective of this study was to retrospectively forecast influenza activity during the year 2020 and assess the impact of COVID-19 public health social measures (PHSMs) on influenza activity and hospital admissions in Hong Kong. Using weekly surveillance data on influenza virus activity in Hong Kong from 2010 to 2019, we developed a statistical modeling framework to forecast influenza virus activity and associated hospital admissions. We conducted short-term forecasts (1-4 weeks ahead) and medium-term forecasts (1-13 weeks ahead) for the year 2020, assuming no PHSMs were implemented against COVID-19. We estimated the reduction in transmissibility, peak magnitude, attack rates, and influenza-associated hospitalization rate resulting from these PHSMs. For short-term forecasts, mean ambient ozone concentration and school holidays were found to contribute to better prediction performance, while absolute humidity and ozone concentration improved the accuracy of medium-term forecasts. We observed a maximum reduction of 44.6% (95% CI: 38.6% - 51.9%) in transmissibility, 75.5% (95% CI: 73.0% - 77.6%) in attack rate, 41.5% (95% CI: 13.9% - 55.7%) in peak magnitude, and 63.1% (95% CI: 59.3% - 66.3%) in cumulative influenza-associated hospitalizations during the winter-spring period of the 2019/2020 season in Hong Kong. The implementation of PHSMs to control COVID-19 had a substantial impact on influenza transmission and associated burden in Hong Kong. Incorporating information on factors influencing influenza transmission improved the accuracy of our predictions.
Subject(s)
COVID-19 , Forecasting , Hospitalization , Influenza, Human , Pandemics , SARS-CoV-2 , Seasons , Humans , Hong Kong/epidemiology , Influenza, Human/epidemiology , Influenza, Human/transmission , COVID-19/epidemiology , COVID-19/transmission , Hospitalization/statistics & numerical data , Forecasting/methods , Retrospective Studies , Models, Statistical , Computational BiologyABSTRACT
Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines and mobile telephones from May 2020 to February 2021. We analyze the epidemiological impact of pandemic fatigue by using the large and detailed cross-sectional telephone surveys to quantify risk perception and self-reported protective behaviors and mathematical models to incorporate population protective behaviors. Our retrospective prediction suggests that an increase of 100 daily new reported cases would lead to 6.60% (95% CI: 4.03, 9.17) more people worrying about being infected, increase 3.77% (95% CI: 2.46, 5.09) more people to avoid social gatherings, and reduce the weekly mean reproduction number by 0.32 (95% CI: 0.20, 0.44). Accordingly, the fourth wave would have been 14% (95% CI%: -53%, 81%) smaller if not for pandemic fatigue. This indicates the important role of mitigating pandemic fatigue in maintaining population protective behaviors for controlling COVID-19.
Subject(s)
COVID-19 , Influenza, Human , Humans , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , Influenza, Human/prevention & control , Hong Kong/epidemiology , Cross-Sectional Studies , Retrospective Studies , Fatigue/epidemiology , Fatigue/prevention & controlABSTRACT
BACKGROUND: The hemagglutination inhibition antibody (HAI) titer contributes only a part of vaccine-induced protection against influenza virus infections. Using causal mediation analysis, we quantified the proportion of vaccine efficacy mediated by postvaccination HAI titers. METHODS: We conducted causal mediation analyses using data from a randomized, active-comparator controlled, phase III, trial of an inactivated, split-virion seasonal quadrivalent influenza vaccine in children conducted from October 2010 to December 2011 in 8 countries. Vaccine efficacy was estimated using a weighted Cox proportional hazards model. Estimates were decomposed into the direct and indirect effects mediated by postvaccination HAI titers. RESULTS: The proportions of vaccine efficacy mediated by postvaccination HAI titers were estimated to be 22% (95% confidence interval, 18%--47%) for influenza A(H1N1), 20% (16%-39%) for influenza A(H3N2), and 37% (26%-85%) for influenza B/Victoria. CONCLUSIONS: HAI titers partially mediate influenza vaccine efficacy against influenza A(H1N1), A(H3N2), and B/Victoria. Our estimates were lower than in previous studies, possibly reflecting expected heterogeneity in antigenic similarity between vaccine and circulating viruses across seasons.
Subject(s)
Antibodies, Viral , Hemagglutination Inhibition Tests , Influenza A Virus, H1N1 Subtype , Influenza A Virus, H3N2 Subtype , Influenza B virus , Influenza Vaccines , Influenza, Human , Vaccine Efficacy , Humans , Influenza Vaccines/immunology , Influenza Vaccines/administration & dosage , Influenza, Human/prevention & control , Influenza, Human/immunology , Influenza A Virus, H1N1 Subtype/immunology , Antibodies, Viral/blood , Antibodies, Viral/immunology , Influenza A Virus, H3N2 Subtype/immunology , Female , Influenza B virus/immunology , Male , Child, Preschool , Child , Infant , Vaccines, Inactivated/immunology , Vaccines, Inactivated/administration & dosageABSTRACT
The time-varying effective reproduction number (Rt at time t) measures the transmissibility of SARS-CoV-2 and is conventionally based on daily case counts, which may suffer from time-varying ascertainment. We analyzed Rt estimates from case counts and severe COVID-19 (intensive care unit admissions, severe or critical cases, and mortality) across 2022 in Hong Kong's fifth and sixth waves of infection. Within the fifth wave, the severe disease-based Rt (3.5) was significantly higher than the case-based Rt (2.4) but not in the sixth wave. During periods with fluctuating underreporting, data based on severe diseases may provide more reliable Rt estimates.
Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Basic Reproduction Number , Time Factors , Outcome Assessment, Health CareABSTRACT
In this cohort study conducted in Hong Kong where both bivalent and monovalent formulations of BNT162b2 were available, there were no significant differences in the mortality or hospitalization between those who received bivalent and monovalent mRNA as second boosters. Bivalent and monovalent mRNA boosters appear equally protective against clinical outcomes.
Subject(s)
BNT162 Vaccine , mRNA Vaccines , Humans , Cohort Studies , Hong Kong , RNA, Messenger , Vaccines, CombinedABSTRACT
BACKGROUND: Studies have reported that repeated annual vaccination may influence influenza vaccination effectiveness in the current season. METHODS: We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. In the first two years, participants received vaccination (V) or saline placebo (P) as follows: P-P, P-V, or V-V. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera collected at 5 timepoints from 95 participants were tested for antibodies against vaccine strains. RESULTS: From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with smaller increases for repeat vaccinees who on average had higher pre-vaccination titers in year 2. There were statistically significant differences in the proportion of participants achieving >=four-fold rises in antibody titer for the repeat vaccinees for influenza A(H1N1), B/Victoria and B/Yamagata, but not for A(H3N2). Among participants who received vaccination in year 2, there were no statistically significant differences between the P-V and V-V groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. CONCLUSIONS: In the first two years, during which influenza did not circulate, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection.
ABSTRACT
We compared the effectiveness and interactions of molnupiravir and nirmatrelvir/ritonavir and 2 vaccines, CoronaVac and Comirnaty, in a large population of inpatients with COVID-19 in Hong Kong. Both the oral antiviral drugs and vaccines were associated with lower risks for all-cause mortality and progression to serious/critical/fatal conditions (study outcomes). No significant interaction effects were observed between the antiviral drugs and vaccinations; their joint effects were additive. If antiviral drugs were prescribed within 5 days of confirmed COVID-19 diagnosis, usage was associated with lower risks for the target outcomes for patients >60, but not <60, years of age; no significant clinical benefit was found if prescribed beyond 5 days. Among patients >80 years of age, 3-4 doses of Comirnaty vaccine were associated with significantly lower risks for target outcomes. Policies should encourage COVID-19 vaccination, and oral antivirals should be made accessible to infected persons within 5 days of confirmed diagnosis.
Subject(s)
COVID-19 , Vaccines , Humans , Child, Preschool , Hong Kong/epidemiology , COVID-19 Vaccines , BNT162 Vaccine , COVID-19 Testing , COVID-19/prevention & control , Antiviral Agents/therapeutic useABSTRACT
We evaluated the population-level benefits of expanding treatment with the antiviral drug Paxlovid (nirmatrelvir/ritonavir) in the United States for SARS-CoV-2 Omicron variant infections. Using a multiscale mathematical model, we found that treating 20% of symptomatic case-patients with Paxlovid over a period of 300 days beginning in January 2022 resulted in life and cost savings. In a low-transmission scenario (effective reproduction number of 1.2), this approach could avert 0.28 million (95% CI 0.03-0.59 million) hospitalizations and save US $56.95 billion (95% CI US $2.62-$122.63 billion). In a higher transmission scenario (effective reproduction number of 3), the benefits increase, potentially preventing 0.85 million (95% CI 0.36-1.38 million) hospitalizations and saving US $170.17 billion (95% CI US $60.49-$286.14 billion). Our findings suggest that timely and widespread use of Paxlovid could be an effective and economical approach to mitigate the effects of COVID-19.
Subject(s)
COVID-19 , Lactams , Leucine , Nitriles , Proline , Public Health , Ritonavir , Humans , United States/epidemiology , SARS-CoV-2 , Antiviral Agents/therapeutic use , Drug CombinationsABSTRACT
To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.
Subject(s)
COVID-19 , Virus Diseases , Humans , COVID-19/epidemiology , SARS-CoV-2 , Pandemics , Public HealthABSTRACT
Modeling studies of household transmission data have helped characterize the role of children in influenza and COVID-19 epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of SARS-CoV-2-like and influenza-like infections in a synthetic population of 1,000 households assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.
ABSTRACT
Prior infection with SARS-CoV-2 can provide protection against infection and severe COVID-19. We aimed to determine the impact of pre-existing immunity on the vaccine effectiveness (VE) estimates. We systematically reviewed and meta-analysed 66 test-negative design (TND) studies that examined VE against infection or severe disease (hospitalization, ICU admission, or death) for primary vaccination series. Pooled VE among studies that included people with prior COVID-19 infection was lower against infection (pooled VE: 77%; 95% confidence interval (CI): 72%, 81%) and severe disease (pooled VE: 86%; 95% CI: 83%, 89%), compared with studies that excluded people with prior COVID-19 infection (pooled VE against infection: 87%; 95% CI: 85%, 89%; pooled VE against severe disease: 93%; 95% CI: 91%, 95%). There was a negative correlation between VE estimates against infection and severe disease, and the cumulative incidence of cases before the start of the study or incidence rates during the study period. We found clear empirical evidence that higher levels of pre-existing immunity were associated with lower VE estimates. Prior infections should be treated as both a confounder and effect modificatory when the policies target the whole population or stratified by infection history, respectively.
ABSTRACT
The serial interval distribution is used to approximate the generation time distribution, an essential parameter to infer the transmissibility (${R}_t$) of an epidemic. However, serial interval distributions may change as an epidemic progresses. We examined detailed contact tracing data on laboratory-confirmed cases of COVID-19 in Hong Kong during the five waves from January 2020 to July 2022. We reconstructed the transmission pairs and estimated time-varying effective serial interval distributions and factors associated with longer or shorter intervals. Finally, we assessed the biases in estimating transmissibility using constant serial interval distributions. We found clear temporal changes in mean serial interval estimates within each epidemic wave studied and across waves, with mean serial intervals ranged from 5.5 days (95% CrI: 4.4, 6.6) to 2.7 (95% CrI: 2.2, 3.2) days. The mean serial intervals shortened or lengthened over time, which were found to be closely associated with the temporal variation in COVID-19 case profiles and public health and social measures and could lead to the biases in predicting ${R}_t$. Accounting for the impact of these factors, the time-varying quantification of serial interval distributions could lead to improved estimation of ${R}_t$, and provide additional insights into the impact of public health measures on transmission.
ABSTRACT
BACKGROUND: The RSVpreF vaccines have breakthrough progress. The respiratory syncytial virus (RSV) vaccine for older adults from GlaxoSmithKline was the first RSV vaccine approved by the US Food and Drug Administration (FDA) in early May 2023, followed by the subsequent FDA approval of Pfizer's RSV vaccines for older adults and pregnant women. We aimed to estimate the public health impact of the potential population-level administrations of the RSVpreF vaccine in the UK. METHODS: In this modelling study, we used national census and contact survey data to construct an individual-based mathematical model, with interpersonal connections characterising household structure, social settings, and age-specific contact patterns. We considered both within-host viral-load dynamics and between-host RSV transmission. We modelled the coverages of RSV vaccines for older people (age ≥60 years) and pregnant women, using influenza vaccination data from the 2018-19 season. We explored a range of possible transmissibility and estimated the health burden averted by RSVpreF vaccine over a 300-day period as compared with the control scenario without vaccines. FINDINGS: In a low-transmission scenario (Re=1·2), RSVpreF would avert a total population of 2·35 (95% credible interval [CrI] 1·24-3·77) million infections, 12.80 (95% CrI 8·60-17·06) thousand hospital admissions, and 0·93 (95% CrI 0·69-1·25) thousand deaths, with 1·82 (1·41-2·33) million infections, 12·44 (8·50-16·38) thousand hospital admissions, and 0·93 (0·67-1·23) thousand deaths averted for people aged 60 years and older. In a high-transmission scenario (Re=2·0), RSVpreF would avert 2·01 (1·37-2·68) million infections, 14·67 (10·05-18·33) thousand hospital admissions, and 1·12 (0·80-1·35) thousand deaths. The majority averted would still be among older adults. INTERPRETATION: Our mathematical models will help improve the vaccine schedules of RSVpreF. Future work will address several limitations when data become available, including the incorporation of population immunity, potential vaccine hesitancy, and other factors affecting vaccine uptake and effectiveness. FUNDING: Government of the Hong Kong Special Administrative Region, the European Research Council, and Ministry of Science and Technology of the People's Republic of China.
Subject(s)
COVID-19 , Respiratory Syncytial Virus Vaccines , Respiratory Syncytial Virus, Human , Humans , Female , Pregnancy , Middle Aged , Aged , Pandemics , United Kingdom/epidemiologyABSTRACT
OBJECTIVE: To determine the effectiveness of nirmatrelvir/ritonavir and molnupiravir among vaccinated and unvaccinated non-hospitalized adults with COVID-19. METHODS: Observational studies of nirmatrelvir/ritonavir or molnupiravir compared to no antiviral drug treatment for COVID-19 in non-hospitalized adults with data on vaccination status were included. We searched MEDLINE, EMBASE, Scopus, Web of Science, WHO COVID-19 Research Database and medRxiv for reports published between 1 January 2022 and 8 November 2023. The primary outcome was a composite of hospitalization or mortality up to 35â days after COVID-19 diagnosis. Risk of bias was assessed with ROBINS-I. Risk ratios (RR), hazard ratios (HR) and risk differences (RD) were separately estimated using random-effects models. RESULTS: We included 30 cohort studies on adults treated with nirmatrelvir/ritonavir (nâ=â462â279) and molnupiravir (nâ=â48â008). Nirmatrelvir/ritonavir probably reduced the composite outcome (RR 0.62, 95%CI 0.55-0.70; I2â=â0%; moderate certainty) with no evidence of effect modification by vaccination status (RR Psubgroupâ=â0.47). In five studies, RD estimates against the composite outcome for nirmatrelvir/ritonavir were 1.21% (95%CI 0.57% to 1.84%) in vaccinated and 1.72% (95%CI 0.59% to 2.85%) in unvaccinated subgroups.Molnupiravir may slightly reduce the composite outcome (RR 0.75, 95%CI 0.67-0.85; I2â=â32%; low certainty). Evidence of effect modification by vaccination status was inconsistent among studies reporting different effect measures (RR Psubgroupâ=â0.78; HR Psubgroupâ=â0.08). In two studies, RD against the composite outcome for molnupiravir were -0.01% (95%CI -1.13% to 1.10%) in vaccinated and 1.73% (95%CI -2.08% to 5.53%) in unvaccinated subgroups. CONCLUSIONS: Among cohort studies of non-hospitalized adults with COVID-19, nirmatrelvir/ritonavir is effective against the composite outcome of severe COVID-19 independent of vaccination status. Further research and a reassessment of molnupiravir use among vaccinated adults are warranted. REGISTRATION: PROSPERO CRD42023429232.
ABSTRACT
This article discusses causal interpretations of epidemiologic studies of the effects of vaccination on sequelae after acute severe acute respiratory syndrome coronavirus 2 infection. To date, researchers have tried to answer several different research questions on this topic. While some studies assessed the impact of postinfection vaccination on the presence of or recovery from post-acute coronavirus disease 2019 syndrome, others quantified the association between preinfection vaccination and postacute sequelae conditional on becoming infected. However, the latter analysis does not have a causal interpretation, except under the principal stratification framework-that is, this comparison can only be interpreted as causal for a nondiscernible stratum of the population. As the epidemiology of coronavirus disease 2019 is now nearly entirely dominated by reinfections, including in vaccinated individuals, and possibly caused by different Omicron subvariants, it has become even more important to design studies on the effects of vaccination on postacute sequelae that address precise causal questions and quantify effects corresponding to implementable interventions.
Subject(s)
COVID-19 , Humans , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , SARS-CoV-2 , Vaccination , Disease ProgressionABSTRACT
Since the emergence of SARS-CoV-2, different variants and subvariants successively emerged to dominate global virus circulation as a result of immune evasion, replication fitness or both. COVID-19 vaccines continue to be updated in response to the emergence of antigenically divergent viruses, the first being the bivalent RNA vaccines that encodes for both the Wuhan-like and Omicron BA.5 subvariant spike proteins. Repeated infections and vaccine breakthrough infections have led to complex immune landscapes in populations making it increasingly difficult to assess the intrinsic neutralizing antibody responses elicited by the vaccines. Hong Kong's intensive COVID-19 containment policy through 2020-2021 permitted us to identify sera from a small number of infection-naïve individuals who received 3 doses of the RNA BNT162b2 vaccine encoding the Wuhan-like spike (WT) and were boosted with a fourth dose of the WT vaccine or the bivalent WT and BA.4/5 spike (WT + BA.4/5). While neutralizing antibody to wild-type virus was comparable in both vaccine groups, BNT162b2 (WT + BA.4/BA.5) bivalent vaccine elicited significantly higher plaque neutralizing antibodies to Omicron subvariants BA.5, XBB.1.5, XBB.1.16, XBB.1.9.1, XBB.2.3.2, EG.5.1, HK.3, BA.2.86 and JN.1, compared to BNT162b2 monovalent vaccine. The single amino acid substitution that differentiates the spike of JN.1 from BA.2.86 resulted in a profound antigenic change.
Subject(s)
BNT162 Vaccine , COVID-19 , Humans , Broadly Neutralizing Antibodies , SARS-CoV-2/genetics , COVID-19 Vaccines , COVID-19/prevention & control , Antibodies, Neutralizing , Vaccination , Antibodies, ViralABSTRACT
From 2020 to December 2022, China implemented strict measures to contain the spread of severe acute respiratory syndrome coronavirus 2. However, despite these efforts, sustained outbreaks of the Omicron variants occurred in 2022. We extracted COVID-19 case numbers from May 2021 to October 2022 to identify outbreaks of the Delta and Omicron variants in all provinces of mainland China. We found that omicron outbreaks were more frequent (4.3 vs. 1.6 outbreaks per month) and longer-lasting (mean duration: 13 vs. 4 weeks per outbreak) than Delta outbreaks, resulting in a total of 865,100 cases, of which 85% were asymptomatic. Despite the average Government Response Index being 12% higher (95% confidence interval (CI): 9%, 15%) in Omicron outbreaks, the average daily effective reproduction number (Rt) was 0.45 higher (95% CI: 0.38, 0.52, p < 0.001) than in Delta outbreaks. Omicron outbreaks were suppressed in 32 days on average (95% CI: 26, 39), which was substantially longer than Delta outbreaks (14 days; 95% CI: 11, 19; p = 0.004). We concluded that control measures effective against Delta could not contain Omicron outbreaks in China. This highlights the need for continuous evaluation of new variants' epidemiology to inform COVID-19 response decisions.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , Disease Outbreaks , China/epidemiologyABSTRACT
Previous studies suggest that influenza virus infection may provide temporary non-specific immunity and hence lower the risk of non-influenza respiratory virus infection. In a randomized controlled trial of influenza vaccination, 1 330 children were followed-up in 2009-2011. Respiratory swabs were collected when they reported acute respiratory illness and tested against influenza and other respiratory viruses. We used Poisson regression to compare the incidence of non-influenza respiratory virus infection before and after influenza virus infection. Based on 52 children with influenza B virus infection, the incidence rate ratio (IRR) of non-influenza respiratory virus infection after influenza virus infection was 0.47 (95% confidence interval: 0.27-0.82) compared with before infection. Simulation suggested that this IRR was 0.87 if the temporary protection did not exist. We identified a decreased risk of non-influenza respiratory virus infection after influenza B virus infection in children. Further investigation is needed to determine if this decreased risk could be attributed to temporary non-specific immunity acquired from influenza virus infection.