Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.

Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology remains unclear. Here, we used a multi-level mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns and to investigate how influenza incidence varies over time, space and age in this population. We estimated median annual influenza infection rates to be approximately 18% from 1968 to 2015, but with substantial variation between years. 88% of individuals were estimated to have been infected at least once during the study period (2009-2015), and 20% were estimated to have three or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long term, epidemiological trends, within-host processes and immunity when analyzed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

SARS-CoV-2 Transmission in Alberta, British Columbia, and Ontario, Canada, January 2020-January 2022.

We estimated COVID-19 transmission potential and case burden by variant type in Alberta, British Columbia, and Ontario, Canada, during January 23, 2020-January 27, 2022; we also estimated the effectiveness of public health interventions to reduce transmission. We estimated time-varying reproduction number (Rt) over 7-day sliding windows and nonoverlapping time-windows determined by timing of policy changes. We calculated incidence rate ratios (IRRs) for each variant and compared rates to determine differences in burden among provinces. Rt corresponding with emergence of the Delta variant increased in all 3 provinces; British Columbia had the largest increase, 43.85% (95% credible interval [CrI] 40.71%-46.84%). Across the study period, IRR was highest for Omicron (8.74 [95% CrI 8.71-8.77]) and burden highest in Alberta (IRR 1.80 [95% CrI 1.79-1.81]). Initiating public health interventions was associated with lower Rt and relaxing restrictions and emergence of new variants associated with increases in Rt.

Comparative analysis of symptom profile and risk of death associated with infection by SARS-CoV-2 and its variants in Hong Kong.

The recurrent multiwave nature of coronavirus disease 2019 (COVID-19) necessitates updating its symptomatology. We characterize the effect of variants on symptom presentation, identify the symptoms predictive and protective of death, and quantify the effect of vaccination on symptom development. With the COVID-19 cases reported up to August 25, 2022 in Hong Kong, an iterative multitier text-matching algorithm was developed to identify symptoms from free text. Multivariate regression was used to measure associations between variants, symptom development, death, and vaccination status. A least absolute shrinkage and selection operator technique was used to identify a parsimonious set of symptoms jointly associated with death. Overall, 70.9% (54 450/76 762) of cases were symptomatic with 102 symptoms identified. Intrinsically, the wild-type and delta variant caused similar symptoms among unvaccinated symptomatic cases, whereas the wild-type and omicron BA.2 subvariant had heterogeneous patterns, with seven symptoms (fatigue, fever, chest pain, runny nose, sputum production, nausea/vomiting, and sore throat) more frequent in the BA.2 cohort. With ≥2 vaccine doses, BA.2 was more likely than delta to cause fever among symptomatic cases. Fever, blocked nose, pneumonia, and shortness of breath remained jointly predictive of death among unvaccinated symptomatic elderly in the wild-type-to-omicron transition. Number of vaccine doses required for reducing occurrence varied by symptoms. We substantiate that omicron has a different clinical presentation compared to previous variants. Syndromic surveillance can be bettered with reduced reliance on symptom-based case identification, increased weighing on symptoms predictive of death in outcome prediction, individual-based risk assessment in care homes, and incorporating free-text symptom reporting.

Global epidemiology of asymptomatic colonisation of methicillin-resistant Staphylococcus aureus in the upper respiratory tract of young children: a systematic review and meta-analysis.

OBJECTIVE: To estimate the global prevalence of asymptomatic colonisation, and determine the associated risk factors, antibiotic resistance and genotypes of methicillin-resistant Staphylococcus aureus (MRSA) in the upper respiratory tract of young children. DESIGN: Four bibliometric databases were searched for publications between 2010 and 2022 according to the protocol registered in PROSPERO. Cross-sectional or cohort studies describing the prevalence of asymptomatic colonisation of S. aureus and MRSA in young children were included. Data extraction and analysis were carried out by two reviewers independently according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. Pooled prevalence was estimated using a random effects model. SETTING AND STUDIES: We included studies where children without respiratory tract infection or Staphylococcal infection were recruited from the community, children's institutions (ie, nurseries, kindergartens, daycare centres and preschools) and healthcare centre visits and assessed for asymptomatic colonisation with S. aureus and MRSA. MAIN OUTCOME MEASURES: The pooled prevalence of asymptomatic colonisation of S. aureus and MRSA of young children globally. RESULTS: In this systematic review and meta-analysis of 21 416 young children, the pooled global prevalence of asymptomatic S. aureus colonisation was 25.1% (95% CI 21.4 to 28.8) and MRSA colonisation was 3.4% (95% CI 2.8 to 4.1). The clones of MRSA strains included healthcare-associated MRSA, community-associated MRSA and livestock-associated MRSA. CONCLUSION: This study provides evidence of increased MRSA colonisation globally among young children, underlining the critical role of asymptomatic carriers in MRSA transmission and the need for control measures. PROSPERO REGISTRATION NUMBER: CRD 42022328385.

The importance of transparency: Declaring the use of generative artificial intelligence (AI) in academic writing.

The integration of generative artificial intelligence (AI) into academic research writing has revolutionized the field, offering powerful tools like ChatGPT and Bard to aid researchers in content generation and idea enhancement. We explore the current state of transparency regarding generative AI use in nursing academic research journals, emphasizing the need for explicitly declaring the use of generative AI by authors in the manuscript. Out of 125 nursing studies journals, 37.6% required explicit statements about generative AI use in their authors' guidelines. No significant differences in impact factors or journal categories were found between journals with and without such requirement. A similar evaluation of medicine, general and internal journals showed a lower percentage (14.5%) including the information about generative AI usage. Declaring generative AI tool usage is crucial for maintaining the transparency and credibility in academic writing. Additionally, extending the requirement for AI usage declarations to journal reviewers can enhance the quality of peer review and combat predatory journals in the academic publishing landscape. Our study highlights the need for active participation from nursing researchers in discussions surrounding standardization of generative AI declaration in academic research writing.

Extracting symptoms from free-text responses using ChatGPT among COVID-19 cases in Hong Kong.

OBJECTIVES: To investigate the feasibility and performance of Chat Generative Pretrained Transformer (ChatGPT) in converting symptom narratives into structured symptom labels. METHODS: We extracted symptoms from 300 deidentified symptom narratives of COVID-19 patients by a computer-based matching algorithm (the standard), and prompt engineering in ChatGPT. Common symptoms were those with a prevalence >10% according to the standard, and similarly less common symptoms were those with a prevalence of 2-10%. The precision of ChatGPT was compared with the standard using sensitivity and specificity with 95% exact binomial CIs (95% binCIs). In ChatGPT, we prompted without examples (zero-shot prompting) and with examples (few-shot prompting). RESULTS: In zero-shot prompting, GPT-4 achieved high specificity (0.947 [95% binCI: 0.894-0.978]-1.000 [95% binCI: 0.965-0.988, 1.000]) for all symptoms, high sensitivity for common symptoms (0.853 [95% binCI: 0.689-0.950]-1.000 [95% binCI: 0.951-1.000]), and moderate sensitivity for less common symptoms (0.200 [95% binCI: 0.043-0.481]-1.000 [95% binCI: 0.590-0.815, 1.000]). Few-shot prompting increased the sensitivity and specificity. GPT-4 outperformed GPT-3.5 in response accuracy and consistent labelling. DISCUSSION: This work substantiates ChatGPT's role as a research tool in medical fields. Its performance in converting symptom narratives to structured symptom labels was encouraging, saving time and effort in compiling the task-specific training data. It potentially accelerates free-text data compilation and synthesis in future disease outbreaks and improves the accuracy of symptom checkers. Focused prompt training addressing ambiguous descriptions impacts medical research positively.

Temporal variations of vaccine hesitancy amid the COVID-19 outbreaks in Hong Kong.

To inform the dynamic adjustments of vaccination campaigns, this study examined the transitions among vaccine hesitancy profiles over the COVID-19 pandemic progression and their predictors and outcomes. The transition patterns among hesitancy profiles over three periods were identified using a latent transition analysis with individuals from a longitudinal cohort study since the emergence of COVID-19 in Hong Kong. Four profiles (i.e., skeptics, apathetics, fence-sitters, and believers) emerged consistently over time. From Period 1 (third and fourth pandemic waves) to Period 2 (dormant period, vaccine rollout), 14.17% of believers became fence-sitters (ambivalization), and 12.11% of fence-sitters became apathetics (apathetization). From Period 2 to Period 3 (omicron surge and vaccine mandates), 20.21% of believers became fence-sitters. Lower trust in government predicted a transition to skepticism, whereas higher trust predicted the opposite. Staying as believers was associated with decreased hygienic and social distancing behavior. The stable hesitancy profiles amid the rapid vaccine uptake suggest that structural factors rather than personal agency may drive the surge. Ambivalization and apathetization may signal disengagement in preventive behaviors. Trust in the government is crucial in the pandemic response. Public health interventions may improve compliance with guidelines and prevent skepticism and apathy.

Revisiting Vaccine Hesitancy in Residential Care Homes for the Elderly for Pandemic Preparedness: A Lesson from COVID-19.

Residents in residential care homes for the elderly (RCHEs) are at high risk of severe illnesses and mortality, while staff have high exposure to intimate care activities. Addressing vaccine hesitancy is crucial to safeguard vaccine uptake in this vulnerable setting, especially amid a pandemic. In response to this, we conducted a cross-sectional survey to measure the level of vaccine hesitancy and to examine its associated factors among residents and staff in RCHEs in Hong Kong. We recruited residents and staff from 31 RCHEs in July-November 2022. Of 204 residents, 9.8% had a higher level of vaccine hesitancy (scored ≥ 4 out of 7, mean = 2.44). Around 7% of the staff (n = 168) showed higher vaccine hesitancy (mean = 2.45). From multi-level regression analyses, higher social loneliness, higher anxiety, poorer cognitive ability, being vaccinated with fewer doses, and lower institutional vaccination rates predicted residents' vaccine hesitancy. Similarly, higher emotional loneliness, higher anxiety, being vaccinated with fewer doses, and working in larger RCHEs predicted staff's vaccine hesitancy. Although the reliance on self-report data and convenience sampling may hamper the generalizability of the results, this study highlighted the importance of addressing the loneliness of residents and staff in RCHEs to combat vaccine hesitancy. Innovative and technology-aided interventions are needed to build social support and ensure social interactions among the residents and staff, especially amid outbreaks.

A longitudinal study of COVID-19 preventive behavior fatigue in Hong Kong: a city with previous pandemic experience.

BACKGROUND: In addition to high vaccination levels, COVID-19 control requires uptake and continued adherence to personal hygiene and social distancing behaviors. It is unclear whether residents of a city with successive experience in worldwide pandemics such as SARS, would quickly adopt and maintain preventive behaviors. METHODS: A population-based, longitudinal telephone survey was conducted between in first local wave of the COVID-19 pandemic (April 2020) and third local wave (December 2020) (n = 403). The study examined factors associated with personal hygiene and social distancing behavior fatigue, as measured by reduced adherence. RESULTS: Over 9 months, face mask use increased (96.5-100%, p < 0.001). Although habitual hand hygiene remained unchanged (92.0%), blue collar workers and non-working individuals showed higher risk of hand hygiene fatigue. There was a decline (p < 0.05) in avoidance of social gatherings (81.1 to 70.7%), avoidance of public places (52.9-27.5%) and avoidance of international travel (81.9-77.4%) even with rising caseloads. Lowered perception of COVID-19 disease severity was associated with decreased avoidance of social gatherings and public places while lower education was associated with decline in avoidance of social gatherings. CONCLUSION: Even in regions with past pandemic experience, maintaining social distancing behaviors during a protracted pandemic remains a major public health challenge.

Alterations in faecal microbiome and resistome in Chinese international travellers: a metagenomic analysis.

BACKGROUND: International travel increases the risk of acquisition of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). Previous studies have characterized the changes in the gut microbiome and resistome of Western travellers; however, information on non-Western populations and the effects of travel-related risk factors on the gut microbiome and resistome remains limited. METHODS: We conducted a prospective observational study on a cohort of 90 healthy Chinese adult residents of Hong Kong. We characterized the microbiome and resistome in stools collected from the subjects before and after travelling to diverse international locations using shotgun metagenomic sequencing and examined their associations with travel-related variables. RESULTS: Our results showed that travel neither significantly changed the taxonomic composition of the faecal microbiota nor altered the alpha (Shannon) or beta diversity of the faecal microbiome or resistome. However, travel significantly increased the number of ARGs. Ten ARGs, including aadA, TEM, mgrB, mphA, qnrS9 and tetR, were significantly enriched in relative abundance after travel, eight of which were detected in metagenomic bins belonging to Escherichia/Shigella flexneri in the post-trip samples. In sum, 30 ARGs significantly increased in prevalence after travel, with the largest changes observed in tetD and a few qnrS variants (qnrS9, qnrS and qnrS8). We found that travel to low- or middle-income countries, or Africa or Southeast Asia, increased the number of ARG subtypes, whereas travel to low- or middle-income countries and the use of alcohol-based hand sanitizer (ABHS) or doxycycline as antimalarial prophylaxis during travel resulted in increased changes in the beta diversity of the faecal resistome. CONCLUSIONS: Our study highlights travel to low- or middle-income countries, Africa or Southeast Asia, a long travel duration, or the use of ABHS or doxycycline as antimalarial prophylaxis as important risk factors for the acquisition/enrichment of ARGs during international travel.

A hybrid machine learning framework to improve prediction of all-cause rehospitalization among elderly patients in Hong Kong.

BACKGROUND: Accurately estimating elderly patients' rehospitalisation risk benefits clinical decisions and service planning. However, research in rehospitalisation and repeated hospitalisation yielded only models with modest performance, and the model performance deteriorates rapidly as the prediction timeframe expands beyond 28 days and for older participants. METHODS: A temporal zero-inflated Poisson (tZIP) regression model was developed and validated retrospectively and prospectively. The data of the electronic health records (EHRs) contain cohorts (aged 60+) in a major public hospital in Hong Kong. Two temporal offset functions accounted for the associations between exposure time and parameters corresponding to the zero-inflated logistic component and the Poisson distribution's expected count. tZIP was externally validated with a retrospective cohort's rehospitalisation events up to 12 months after the discharge date. Subsequently, tZIP was validated prospectively after piloting its implementation at the study hospital. Patients discharged within the pilot period were tagged, and the proposed model's prediction of their rehospitalisation was verified monthly. Using a hybrid machine learning (ML) approach, the tZIP-based risk estimator's marginal effect on 28-day rehospitalisation was further validated, competing with other factors representing different post-acute and clinical statuses. RESULTS: The tZIP prediction of rehospitalisation from 28 days to 365 days was achieved at above 80% discrimination accuracy retrospectively and prospectively in two out-of-sample cohorts. With a large margin, it outperformed the Cox proportional and linear models built with the same predictors. The hybrid ML revealed that the risk estimator's contribution to 28-day rehospitalisation outweighed other features relevant to service utilisation and clinical status. CONCLUSIONS: A novel rehospitalisation risk model was introduced, and its risk estimators, whose importance outweighed all other factors of diverse post-acute care and clinical conditions, were derived. The proposed approach relies on four easily accessible variables easily extracted from EHR. Thus, clinicians could visualise patients' rehospitalisation risk from 28 days to 365 days after discharge and screen high-risk older patients for follow-up care at the proper time.

Does ACE2 mediate the detrimental effect of exposures related to COVID-19 risk: A Mendelian randomization investigation.

OBJECTIVES: Adiposity, smoking, and lower socioeconomic position (SEP) increase COVID-19 risk while the association of vitamin D, blood pressure, and glycemic traits in COVID-19 risk were less clear. Whether angiotensin-converting enzyme 2 (ACE2), the key receptor for SARS-CoV-2, mediates these associations has not been investigated. We conducted a Mendelian randomization study to assess the role of these exposures in COVID-19 and mediation by ACE2. METHODS: We extracted genetic variants strongly related to various exposures (vitamin D, blood pressure, glycemic traits, smoking, adiposity, and educational attainment [SEP proxy]), and ACE2 cis-variants from genome-wide association studies (GWAS, n ranged from 28 204 to 3 037 499) and applied them to GWAS summary statistics of ACE2 (n = 28 204) and COVID-19 (severe, hospitalized, and susceptibility, n ≤ 2 942 817). We used inverse variance weighted as the main analyses, with MR-Egger and weighted median as sensitivity analyses. Mediation analyses were performed based on product of coefficient method. RESULTS: Higher adiposity, lifetime smoking index, and lower educational attainment were consistently associated with higher risk of COVID-19 phenotypes while there was no strong evidence for an association of other exposures in COVID-19 risk. ACE2 partially mediates the detrimental effects of body mass index (ranged from 4.3% to 8.2%), waist-to-hip ratio (ranged from 11.2% to 16.8%), and lower educational attainment (ranged from 4.0% to 7.5%) in COVID-19 phenotypes while ACE2 did not mediate the detrimental effect of smoking. CONCLUSIONS: We provided genetic evidence that reducing ACE2 could partly lower COVID-19 risk amongst people who were overweight/obese or of lower SEP.

Amplifying research influence through the social network, open access publishing, and international collaboration: A mediation analysis on nursing studies literature.

INTRODUCTION: Research impact and influence are commonly measured quantitatively by citation count received by research articles. Many institutes also use citation count as one of the factors in faculty performance appraisal and candidate selection of academic positions. Various strategies were recommended to amplify and accelerate research influence, particularly citation counts, by bringing research articles to a wider reach for potential readers. However, no prior empirical study was conducted to examine and valid effects of those strategies on nursing studies. This study examines and verifies the direct effects and mediation effects of some strategies, namely, the use of Twitter, international collaboration, the use of ResearchGate, and open access publishing, for amplifying the citation of research and review articles in nursing studies. DESIGN: Cross-sectional study design. METHODS: Articles published in top nursing journals in 2016 were identified in PUBMED and the citation metrics for individual articles until 2021 were extracted from Scopus. The primary outcome was the citation count of the article, while the tweet count on Twitter of the article was considered a mediator. The predictors included paper type, the total number of authors, the proportion of authors with a ResearchGate account in the article, funding support, open-accessed article, and the number of different countries stated in the authors' affiliation. A mediation analysis was conducted to examine the predictors' direct and indirect effects (i.e., via tweet count) on the citation count of the article. RESULTS: A total of 2210 articles were included in this study, of which 223 (10.1%) were review articles. The median (IQR) number of Scopus citations, tweets, countries, and percentage of authors with ResearchGate accounts were 12 (6-21), 2 (0-6), 1 (1-1), and 75% (50%-100%) respectively. In the mediation analysis, tweet count, article type, number of countries, percentage of authors with a ResearchGate account, and journal impact factors in 2014 were positively associated with the Scopus citation count. The effects of article type, open access, and journals' impact factors in 2014 on Scopus citation count were mediated by the tweet count. CONCLUSION: This study provides empirical support for some strategies researchers may employ to amplify the citation count of their research articles. The methodology of our study can be extended to compare research influence between entities (e.g., across countries or institutes). CLINICAL RELEVANCE: The citation refers to the research work cited by peers and is one of the indicators for research impact. Higher citations implied the research work is read and used by others, therefore, understanding the associated factors with higher citations is critical.

Age-related seroprevalence trajectories of seasonal coronaviruses in children including neonates in Guangzhou, China.

OBJECTIVES: Four seasonal coronaviruses, including human coronavirus (HCoV)-229E and HCoV-OC43, HCoV-NL63, and HCoV-HKU1 cause approximately 15-30% of common colds in adults. However, the full landscape of the immune trajectory to these viruses that covers the whole childhood period is still not well understood. METHODS: We evaluated the serological responses against the four seasonal coronaviruses in 1886 children aged under 18 years by using enzyme-linked immunosorbent assay. The optical density values against each HCoV were determined from each sample. Generalized additive models were constructed to determine the relationship between age and seroprevalence throughout the whole childhood period. The specific antibody levels against the four seasonal coronaviruses were also tested from the plasma samples of 485 pairs of postpartum women and their newborn babies. RESULTS: The immunoglobulin (Ig) G levels of the four seasonal coronaviruses in the mother and the newborn babies were highly correlated (229E: r = 0.63; OC43: r = 0.65; NL63: r = 0.69; HKU1: r = 0.63). The seroprevalences in children showed a similar trajectory in that the levels of IgG in the neonates dropped significantly and reached the lowest level after the age of around 1 year (229E: 1.18 years; OC43: 0.97 years; NL63: 1.01 years; HKU1: 1.02 years) and then resurgence in the children who aged older than 1 year. Using the lowest level from the generalized additive models as our cutoff, the seroprevalences for HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1 were 98.11%, 96.23%, 96.23% and 94.34% at the age of 16-18 years. CONCLUSION: Mothers share HCoV-specific IgGs with their newborn babies and the level of maternal IgGs waned at around 1 year after birth. The resurgence of the HCoV-specific IgGs was found thereafter with the increase in age suggesting repeated infection occurred in children.

The way forward to achieve high COVID-19 vaccination and revaccination coverage in a city amid a period of tranquility.

Background: Amid the current COVID-19 pandemic, there is an urgent need for both vaccination and revaccination ("boosting"). This study aims to identify factors associated with the intention to receive a booster dose of the coronavirus (COVID-19) vaccine among individuals vaccinated with two doses and characterize their profiles in Hong Kong, a city with a low COVID-19 incidence in the initial epidemic waves. Among the unvaccinated, vaccination intention is also explored and their profiles are investigated. Methods: From December 2021 - January 2022, an online survey was employed to recruit 856 Hong Kong residents aged 18 years or over from an established population-based cohort. Latent class analysis and multivariate logistic regression modeling approaches were used to characterize boosting intentions. Results: Of 638 (74.5%) vaccinated among 856 eligible subjects, 42.2% intended to receive the booster dose. Four distinct profiles emerged with believers having the highest intention, followed by apathetics, fence-sitters and skeptics. Believers were older and more likely to have been vaccinated against influenza. Older age, smoking, experiencing no adverse effects from a previous COVID-19 vaccination, greater confidence in vaccines and collective responsibility, and fewer barriers in accessing vaccination services were associated with higher intentions to receive the booster dose. Of 218 unvaccinated, most were fence-sitters followed by apathetics, skeptics, and believers. Conclusion: This study foretells the booster intended uptake lagging initial vaccination across different age groups and can help refine the current or future booster vaccination campaign. Given the fourth COVID-19 vaccine dose may be offered to all adults, strategies for improving boosting uptake include policies targeting young adults, individuals who experienced adverse effects from previous doses, fence-sitters, apathetics, and the general public with low trust in the health authorities.

Path to normality: Assessing the level of social-distancing measures relaxation against antibody-resistant SARS-CoV-2 variants in a partially-vaccinated population.

Introduction: Two years into the coronavirus 2019 (COVID-19) pandemic, populations with less built-up immunity continued to devise ways to optimize social distancing measures (SDMs) relaxation levels for outbreaks triggered by SARS-CoV-2 and its variants to resume minimal economics activities while avoiding hospital system collapse. Method: An age-stratified compartmental model featuring social mixing patterns was first fitted the incidence data in second wave in Hong Kong. Hypothetical scenario analysis was conducted by varying population mobility and vaccination coverages (VCs) to predict the number of hospital and intensive-care unit admissions in outbreaks initiated by ancestral strain and its variants (Alpha, Beta, Gamma, Delta and Omicron). Scenarios were "unsustainable" if either of admissions was larger than the maximum of its occupancy. Results: At VC of 65%, scenarios of full SDMs relaxation (mean daily social encounters prior to COVID-19 pandemic = 14.1 contacts) for outbreaks triggered by ancestral strain, Alpha and Beta were sustainable. Restricting levels of SDMs was required such that the optimal population mobility had to be reduced to 0.9, 0.65 and 0.37 for Gamma, Delta and Omicron associated outbreaks respectively. VC improvement from 65% to 75% and 95% allowed complete SDMs relaxation in Gamma-, and Delta-driven epidemic respectively. However, this was not supported for Omicron-triggered epidemic. Discussion: To seek a path to normality, speedy vaccine and booster distribution to the majority across all age groups is the first step. Gradual or complete SDMs lift could be considered if the hybrid immunity could be achieved due to high vaccination coverage and natural infection rate among vaccinated or the COVID-19 case fatality rate could be reduced similar to that for seasonal influenza to secure hospital system sustainability.

Estimation of local transmissibility in the early phase of monkeypox epidemic in 2022.

OBJECTIVES: To estimate the basic reproductive number (Ro) to help us understand and control the spread of monkeypox in immunologically naive populations. METHODS: Using three highest incidence populations including England, Portugal, and Spain as examples as of 18 June 2022, we employed the branching process with a Poisson likelihood and gamma-distributed serial interval to fit daily reported case data of monkeypox to estimate Ro. Sensitivity analyses were performed by varying mean serial interval from 6.8 to 12.8 days. RESULTS: The median posterior estimates of Ro for monkeypox in the three study populations were statistically >1 (England: Ro = 1.60 [95% (credible interval) CrI, 1.50-1.70]; Portugal: Ro = 1.40 [95% CrI, 1.20-1.60]; Spain: Ro = 1.80 [95% CrI, 1.70-2.00]). Ro estimates varied over 1.30 to 2.10, depending on the serial interval. DISCUSSION: The updated Ro estimates across different populations will inform policy makers' plans for public health control measures. Currently, monkeypox has a sustainable outbreak potential and may challenge healthcare systems, mainly due to declines in the population level immunity to Orthopoxviruses since the cessation of routine smallpox vaccination. Smallpox vaccination has been shown to be effective in protecting (≤85% effectiveness) against monkeypox infection in earlier times. So early postexposure vaccination is currently being offered in an attempt to control its spread.