Specific lateral flow detection of isothermal nucleic acid amplicons for accurate point-of-care testing.

For point-of-care testing (POCT), coupling isothermal nucleic acid amplification schemes (e.g., recombinase polymerase amplification, RPA) with lateral flow assay (LFA) readout is an ideal platform, since such integration offers both high sensitivity and deployability. However, isothermal schemes typically suffers from non-specific amplification, which is difficult to be differentiated by LFA and thus results in false-positives. Here, we proposed an accurate POCT platform by specific recognition of target amplicons with peptide nucleic acid (PNA, assisted by T7 Exonuclease), which could be directly plugged into the existing RPA kits and commercial LFA test strips. With SARS-CoV-2 as the model, the proposed method (RPA-TeaPNA-LFA) efficiently eliminated the false-positives, exhibiting a lowest detection concentration of 6.7 copies/µL of RNA and 90 copies/µL of virus. Using dual-gene (orf1ab and N genes of SARS-CoV-2) as the targets, RPA-TeaPNA-LFA offered a high specificity (100%) and sensitivity (RT-PCR Ct < 31, 100%; Ct < 40, 71.4%), and is valuable for on-site screening or self-testing during isolation. In addition, the dual test lines in the test strips were successfully explored for simultaneous detection of SARS-CoV-2 and H1N1, showing great potential in response to future pathogen-based pandemics.

Residential clustering of COVID-19 cases and efficiency of building-wide compulsory testing notices as a transmission control measure in Hong Kong.

We described the frequency of residential case clusters and the efficiency of compulsory testing in identifying cases using buildings targeted in compulsory testing and locally infected COVID-19 cases matched by residence in Hong Kong. Most of the buildings (4246/7688, 55.2%) with COVID-19 cases identified had only one reported case and 13% of the daily reported cases were detected through compulsory testing. Compulsory testing notices could be essential in attempting to eliminate infections ('zero covid') and impactful early in an epidemic but appears to be relatively inefficient in response to sustained community transmission.

Real-World COPD Management Over 3 Years at the Community Health Service Center of Shanghai During the COVID-19 Pandemic in China.

Objective: To evaluate the real-world situation for the management of chronic obstructive pulmonary disease (COPD) and poorly controlled disease risk factors in the Chinese community. Methods: This retrospective multicentre study analysed data from COPDMICand MICHC in Shanghai Songjiang District, Shanghai, China. The differences in COPD Assessment Test (CAT), the modified Medical Research Council (mMRC) dyspnea scale, and the number of emergency cases, emergency visits, inpatient cases, and hospitalisations from January 2018 to December 2020 were analysed. The impact of coronavirus disease 2019 (COVID-19) on COPD management was also assessed. Results: For 2020 versus 2018, analysis of 468 COPD cases from COPDMIC matched with MICHC data showed significantly more patients with improved mMRC grades, significantly fewer emergency cases and emergency visits, and significantly fewer hospitalisation cases and hospitalisations. Differences in the number of emergency visits and hospitalisations per capita were statistically significant. Compared to GOLD 3-4, GOLD 1-2 patients showed significant improvements in CAT score, mMRC grade, the number of emergency visits and hospitalisations per capita. Treatment adherence from 2018 to 2020 was 25%, 29.1%, and 6.8%, and the proportion of medication regimens consistent with guidelines was 43.44%, 50.98%, and 71.87%, respectively. Higher treatment adherence resulted in significantly improved CAT scores and mMRC grades and fewer emergency department visits and hospitalisations per capita. Conclusion: Combined with remote management tools, patients with COPD achieved continuous improvement in symptoms and exacerbations over 3 years. In the context of COVID-19 prevention/control measures, improvements were significant for patients with GOLD 1-2 COPD but limited with GOLD 3-4. Pharmacologic treatment significantly improved clinical symptoms and reduced emergency visits and hospitalisations. Severe airflow limitation and poor adherence to pharmacologic treatment were important risk factors for lack of disease remission.

Large-scale emergency medical services scheduling during the outbreak of epidemics.

This paper studies a new large-scale emergency medical services scheduling (EMSS) problem during the outbreak of epidemics like COVID-19, which aims to determine an optimal scheduling scheme of emergency medical services to minimize the completion time of nucleic acid testing to achieve rapid epidemic interruption. We first analyze the impact of the epidemic spread and assign different priorities to different emergency medical services demand points according to the degree of urgency. Then, we formulate the EMSS as a mixed-integer linear program (MILP) model and analyze its complexity. Given the NP-hardness of the problem, we develop two fast and effective improved discrete artificial bee colony algorithms (IDABC) based on problem properties. Experimental results for a real case and practical-sized instances with up to 100 demand points demonstrate that the IDABC significantly outperforms MILP solver CPLEX and two state-of-the-art metaheuristic algorithms in both solution quality and computational efficiency. In addition, we also propose some managerial implications to support emergency management decision-making.

Identification of natural compounds as SARS-CoV-2 inhibitors via molecular docking and molecular dynamic simulation.

Background: Base mutations increase the contagiousness and transmissibility of the Delta and Lambda strains and lead to the severity of the COVID-19 pandemic. Molecular docking and molecular dynamics (MD) simulations are frequently used for drug discovery and relocation. Small molecular compounds from Chinese herbs have an inhibitory effect on the virus. Therefore, this study used computational simulations to investigate the effects of small molecular compounds on the spike (S) protein and the binding between them and angiotensin-converting enzyme 2 (ACE2) receptors. Methods: In this study, molecular docking, MD simulation, and protein-protein analysis were used to explore the medicinal target inhibition of Chinese herbal medicinal plant chemicals on SARS-CoV-2. 12,978 phytochemicals were screened against S proteins of SARS-CoV-2 Lambda and Delta mutants. Results: Molecular docking showed that 65.61% and 65.28% of the compounds had the relatively stable binding ability to the S protein of Lambda and Delta mutants (docking score ≤ -6). The top five compounds with binding energy with Lambda and Delta mutants were clematichinenoside AR2 (-9.7), atratoglaucoside,b (-9.5), physalin b (-9.5), atratoglaucoside, a (-9.4), Ochnaflavone (-9.3) and neo-przewaquinone a (-10), Wikstrosin (-9.7), xilingsaponin A (-9.6), ardisianoside G (-9.6), and 23-epi-26-deoxyactein (-9.6), respectively. Four compounds (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) could interact with S protein mutation sites of Lambda and Delta mutants, respectively, and MD simulation results showed that four plant chemicals and spike protein have good energy stable complex formation ability. In addition, protein-protein docking was carried out to evaluate the changes in ACE2 binding ability caused by the formation of four plant chemicals and S protein complexes. The analysis showed that the binding of four plant chemicals to the S protein could reduce the stability of the binding to ACE2, thereby reducing the replication ability of the virus. Conclusion: To sum up, the study concluded that four phytochemicals (Casuarictin, Heterophylliin D, Protohypericin, and Glansrin B) had significant effects on the binding sites of the SARS-CoV-2 S protein. This study needs further in vitro and in vivo experimental validation of these major phytochemicals to assess their potential anti-SARS-CoV-2. Graphical abstract.

One Health Surveillance of Antimicrobial Use and Resistance: Challenges and Successes of Implementing Surveillance Programs in Sri Lanka.

BACKGROUND: Sri Lanka is a low-income country, as defined by the World Bank. The country suffered further economic downturn during the COVID-19 pandemic. This situation adversely affected the prioritization of policies and programs around healthcare and public health. In particular, inflation, fuel prices, and shortage of food supplies increased struggles to implement antimicrobial resistance (AMR) programs. However, in the long run, it is crucial to gather data and evidence to plan AMR policies and track interventions. (1) Aim: To establish and reiterate the importance of prioritizing AMR programs in the One Health framework, the Fleming Fellows collected and studied antimicrobial use/consumption (AMU/AMC) and resistance (AMR) in humans, food-producing animals, and the environment. (2) Methods: A systematic and cross-sectional study was conducted between 2019 and 2021. By way of coordinating an AMU/AMC and AMR prevalence study across six agencies from human health and food-producing animal sectors, the authors established a field epidemiology study, laboratory testing, and data processing at their institutions. AMU/AMC patterns were surveyed using questionnaires and interviews, while AMR samples were collected for antibiotic susceptibility tests and genomic tests. Samples were tested for phenotypic and genotypic resistance. (3) Results: In human samples, resistance was highest to beta-lactam antibiotics. In non-human samples, resistance was highest to erythromycin, a highest-priority, critically important antibiotic defined by the World Health Organization. From government records, tylosin was sold the most in the food-producing animal sector. (4) Conclusions: Sri Lanka AMU and AMR trends in human and non-human sectors can be ascertained by a One Health framework. Further coordinated, consistent, and sustainable planning is feasible, and can help implement an AMU/AMR surveillance system in Sri Lanka.

Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong.

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.

Characterizing Human Collective Behaviors During COVID-19 - Hong Kong SAR, China, 2020.

What is already known about this topic?: People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. What is added by this report?: This study offers a framework for evaluating interactions among individuals' emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model's output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. What are the implications for public health practice?: Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people's risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives.

Risk of within-hotel transmission of SARS-CoV-2 during on-arrival quarantine in Hong Kong: an epidemiological and phylogenomic investigation.

Background: On-arrival quarantine has been one of the primary measures to prevent the introduction of SARS-CoV-2 into Hong Kong since the start of the pandemic. Most on-arrival quarantines have been done in hotels, with the duration of quarantine and testing frequency during quarantine modified over time along with other pandemic control measures. However, hotels are not designed with infection control in mind. We aimed to systematically study the potential risk of acquisition of SARS-CoV-2 infection among individuals undergoing hotel quarantine. Methods: We examined data on each laboratory-confirmed COVID-19 case identified in on-arrival quarantine in a hotel in Hong Kong between 1 May 2020 and 31 January 2022. We sequenced the whole genomes of viruses from cases that overlapped with other confirmed cases in terms of the hotel of stay, date of arrival and date of testing positive. By combining multiple sources of evidence, we identify probable and plausible transmission events and calculate the overall risk of transmission. Findings: Among 221 imported cases that overlapped with other cases detected during hotel quarantine with available sequence data, phylogenomic analyses identified five probable and two plausible clusters of within-hotel transmission. Only two of these clusters were recognised at the time. Including other clusters reported in Hong Kong, we estimate that 8-11 per 1000 cases identified in hotel quarantine may be infected by another unlinked case during quarantine, or 2-3 per 100,000 overseas arrivals. Interpretation: We have identified additional undetected occurrences of COVID-19 transmission within hotel quarantine in Hong Kong. Although hotels provide suboptimal infection control as improvised quarantine facilities, the risk of contracting infection whilst in quarantine is low. However, these unlikely events could have high consequences by allowing the virus to spread into immunologically naïve communities. Additional vigilance should be taken in the absence of improved controls to identify such events. If on-arrival quarantine is expected to be used for a long time, quarantine facilities could be purpose-built to minimise the risk of transmission. Funding: Health and Medical Research Fund, Hong Kong.

Inferring time-varying generation time, serial interval, and incubation period distributions for COVID-19.

The generation time distribution, reflecting the time between successive infections in transmission chains, is a key epidemiological parameter for describing COVID-19 transmission dynamics. However, because exact infection times are rarely known, it is often approximated by the serial interval distribution. This approximation holds under the assumption that infectors and infectees share the same incubation period distribution, which may not always be true. We estimated incubation period and serial interval distributions using 629 transmission pairs reconstructed by investigating 2989 confirmed cases in China in January-February 2020, and developed an inferential framework to estimate the generation time distribution that accounts for variation over time due to changes in epidemiology, sampling biases and public health and social measures. We identified substantial reductions over time in the serial interval and generation time distributions. Our proposed method provides more reliable estimation of the temporal variation in the generation time distribution, improving assessment of transmission dynamics.

Adaptor protein MyD88 confers the susceptibility to stress via amplifying immune danger signals.

Increasing evidence supports the pathogenic role of neuroinflammation in psychiatric diseases, including major depressive disorder (MDD) and neuropsychiatric symptoms of Coronavirus disease 2019 (COVID-19); however, the precise mechanism and therapeutic strategy are poorly understood. Here, we report that myeloid differentiation factor 88 (MyD88), a pivotal adaptor that bridges toll-like receptors to their downstream signaling by recruiting the signaling complex called 'myddosome', was up-regulated in the medial prefrontal cortex (mPFC) after exposure to chronic social defeat stress (CSDS) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. The inducible expression of MyD88 in the mPFC primed neuroinflammation and conferred stress susceptibility via amplifying immune danger signals, such as high-mobility group box 1 and SARS-CoV-2 spike protein. Overexpression of MyD88 aggravated, whereas knockout or pharmacological inhibition of MyD88 ameliorated CSDS-induced depressive-like behavior. Notably, TJ-M2010-5, a novel synthesized targeting inhibitor of MyD88 dimerization, alleviated both CSDS- and SARS-CoV-2 spike protein-induced depressive-like behavior. Taken together, our findings indicate that inhibiting MyD88 signaling represents a promising therapeutic strategy for stress-related mental disorders, such as MDD and COVID-19-related neuropsychiatric symptoms.

Hospitalizations and mortality during the first year of the COVID-19 pandemic in Hong Kong, China: An observational study

Summary Background Hong Kong followed a strict COVID-19 elimination strategy in 2020. We estimated the impact of the COVID-19 pandemic responses on all-cause and cause-specific hospitalizations and deaths in 2020. Methods Interrupted time-series analysis using negative binomial regression accounting for seasonality and long-term trend was used on weekly 2010–2020 data to estimate the change in hospitalization risk and excess mortality occurring both within and out of hospitals. Findings In 2020, as compared to a 2010–2019 baseline, we observed an overall reduction in all-cause hospitalizations, and a concurrent increase in deaths. The overall hospitalization reduction (per 100,000 population) was 4809 (95% CI: 4692, 4926) in 2020, with respiratory diseases (632, 95% CI: 607, 658) and cardiovascular diseases (275, 95% CI: 264, 286) contributing most. The overall excess mortality (per 100,000 population) was 25 (95% CI: 23, 27) in 2020, mostly among individuals with pre-existing cardiovascular diseases (12, 95% CI: 11, 13). A reduction in excess in-hospital mortality (−10 per 100,000, 95% CI: −12, −8) was accompanied by an increase in excess out-of-hospital mortality (32, 95% CI: 29, 34). Interpretation The COVID-19 pandemic might have caused indirect impact on population morbidity and mortality likely through changed healthcare seeking particularly in youngest and oldest individuals and those with cardiovascular diseases. Better healthcare planning is needed during public health emergencies with disruptions in healthcare services. Funding Health and Medical Research Fund, Collaborative Research Fund, AIR@InnoHK and RGC Senior Research Fellow Scheme, Hong Kong.

Sodium alginate-hydrogel coatings on extracorporeal membrane oxygenation for anticoagulation.

Thromboembolism caused by the use of extracorporeal membrane oxygenation (ECMO) remains common among patients with existing heart diseases and contributes to significant morbidity and mortality during the COVID-19 pandemic. Various surface modification strategies have been proposed, showing that the methacrylated alginate (MA-SA) hydrogel layer is transparent, which aids the observation of the thromboembolism from the inner wall of the tubing. In the combined dynamic and static blood of ECMO tubing inner surface in vitro experiments, it was also demonstrated that the adhesion of blood clots to the surface of vessels was remarkably reduced, and the MA-SA-based hydrogel coating could significantly prolong the activated partial thrombin time and block the endogenous coagulation. The favorable properties of natural polysaccharides of hydrogel coatings make them the best surface material choices to be applied for blood-contacting medical devices and significantly improve anticoagulant performance.

Transmission dynamics of SARS-CoV-2 Omicron variant infections in Hangzhou, Zhejiang, China, January-February 2022.

OBJECTIVES: We aimed to explore the transmission dynamics of the Omicron BA.1.1 variant in an outbreak in China. METHODS: We constructed 113 transmission pairs based on the time of exposure and symptom onset for identified infectors and infectees, using the epidemiological data collected during an outbreak in Hangzhou, Zhejiang province, China, between January and February 2022. The key epidemiological parameters were estimated. RESULTS: The mean estimates of the incubation period and latent period distributions were 3.8 days (95% credible interval: 3.5, 4.1) and 3.1 days (2.8, 3.5), respectively. The overall transmission risk peaked at symptom onset, and we estimated that 33.6% (24.8, 42.5) of transmission occurred before symptom onset. The forward generation time decreased from 5.2 days (4.7, 5.7) at the start of the outbreak to 2.2 days (2.0, 2.5) by the end. Allowing this variation over time in the generation time distribution, we estimated that the reproduction number dropped rapidly from 9.5 (3.5, 18.4) to 0.8 (0.3, 1.5) over the outbreak. CONCLUSION: Shorter incubation period and latent period were estimated for the Omicron BA.1.1 variant. Stringent public health measures prevented a large epidemic by reducing transmission, as indicated by the shortened generation time.

Prediction of upcoming global infection burden of influenza seasons after relaxation of public health and social measures during the COVID-19 pandemic: a modelling study.

BACKGROUND: The transmission dynamics of influenza were affected by public health and social measures (PHSMs) implemented globally since early 2020 to mitigate the COVID-19 pandemic. We aimed to assess the effect of COVID-19 PHSMs on the transmissibility of influenza viruses and to predict upcoming influenza epidemics. METHODS: For this modelling study, we used surveillance data on influenza virus activity for 11 different locations and countries in 2017-22. We implemented a data-driven mechanistic predictive modelling framework to predict future influenza seasons on the basis of pre-COVID-19 dynamics and the effect of PHSMs during the COVID-19 pandemic. We simulated the potential excess burden of upcoming influenza epidemics in terms of fold rise in peak magnitude and epidemic size compared with pre-COVID-19 levels. We also examined how a proactive influenza vaccination programme could mitigate this effect. FINDINGS: We estimated that COVID-19 PHSMs reduced influenza transmissibility by a maximum of 17·3% (95% CI 13·3-21·4) to 40·6% (35·2-45·9) and attack rate by 5·1% (1·5-7·2) to 24·8% (20·8-27·5) in the 2019-20 influenza season. We estimated a 10-60% increase in the population susceptibility for influenza, which might lead to a maximum of 1-5-fold rise in peak magnitude and 1-4-fold rise in epidemic size for the upcoming 2022-23 influenza season across locations, with a significantly higher fold rise in Singapore and Taiwan. The infection burden could be mitigated by additional proactive one-off influenza vaccination programmes. INTERPRETATION: Our results suggest the potential for substantial increases in infection burden in upcoming influenza seasons across the globe. Strengthening influenza vaccination programmes is the best preventive measure to reduce the effect of influenza virus infections in the community. FUNDING: Health and Medical Research Fund, Hong Kong.

Lineage-specific positive selection on ACE2 contributes to the genetic susceptibility of COVID-19.

The Angiotensin-Converting Enzyme-2 (ACE2) gene, located on Xp22.2, attracts a great deal of attention because the protein it encodes is believed to be the functional cellular receptor for the new coronavirus (SARS-CoV-2). However, recent studies are controversial, especially concerning the intrinsic link between ACE2 diversity and COVID-19 susceptibility. Here, we conduct a population genetic study on ACE2 in 6354 individuals representing 210 present-day populations and 5329 individuals of ancient or archaic groups. We dissected the genetic architecture of ACE2 and identified two major haplogroups (hg) in East Asians, i.e. ACE2-hg1 (43%) and ACE2-hg2 (53%), while other populations harbor more diverse ACE2-hgs. Accordingly, there was a significant loss of ACE2 common variations in East Asians in contrast to the X-chromosome-wide and genome-wide patterns. Notably, association analysis between ACE2-hgs and COVID-19 severity in 1229 Han Chinese individuals with various levels of COVID-19 severity showed a higher risk of ACE2-hg1 (odds ratio = 1.56, P < 0.01) and a lower risk of ACE2-hg2 (odds ratio = 0.65, P < 0.01). Interestingly, ACE2-hg1 is in strong linkage disequilibrium with rs1849863-C, which is an assumed risk factor of elevated plasma ACE2 level and is related to a higher risk of COVID-19 severity, hospitalization and infection. Strikingly, remarkable signatures of positive selection were detected, especially on ACE2-hg2, and were traced back to 100 000 years ago (but rose to a strong level during the Bronze Age, 5000∼3000 years ago, in East Asians). The selection pressures could have stemmed from multiple sources, but pre-COVID-19 viral epidemics and pandemics might have been potential driving forces, which consequently contributed to the genetic susceptibility to COVID-19 within and between populations.

Spatial and temporal dynamics of SARS-CoV-2: Modeling, analysis and simulation.

A reaction-diffusion viral infection model is formulated to characterize the infection process of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a heterogeneous environment. In the model, the viral production, infection and death rates of compartments are given by the general functions. We consider the well-posedness of the solution, derive the basic reproduction number R 0 , discuss the global stability of uninfected steady state and explore the uniform persistence for the model. We further propose a spatial diffusion SARS-CoV-2 infection model with humoral immunity and spatial independent coefficients, and analyze the global attractivity of uninfected, humoral inactivated and humoral activated equilibria which are determined by two dynamical thresholds. Numerical simulations are performed to illustrate our theoretical results which reveal that diffusion, spatial heterogeneity and incidence types have evident impact on the SARS-CoV-2 infection process which should not be neglected for experiments and clinical treatments.

Reproduction Numbers of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants: A Systematic Review and Meta-analysis.

The coronavirus disease 2019 (COVID-19) pandemic continues to pose substantial risks to public health, worsened by the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that may have a higher transmissibility and reduce vaccine effectiveness. We conducted a systematic review and meta-analysis on reproduction numbers of SARS-CoV-2 variants and provided pooled estimates for each variant.

Universal Community Nucleic Acid Testing for Coronavirus Disease 2019 (COVID-19) in Hong Kong Reveals Insights Into Transmission Dynamics: A Cross-Sectional and Modeling Study.

BACKGROUND: Testing of an entire community has been used as an approach to control coronavirus disease 2019 (COVID-19). In Hong Kong, a universal community testing program (UCTP) was implemented at the fadeout phase of a community epidemic in July to September 2020. We described the utility of the UCTP in finding unrecognized infections and analyzed data from the UCTP and other sources to characterize transmission dynamics. METHODS: We described the characteristics of people participating in the UCTP and compared the clinical and epidemiological characteristics of COVID-19 cases detected by the UCTP versus those detected by clinical diagnosis and public health surveillance (CDPHS). We developed a Bayesian model to estimate the age-specific incidence of infection and the proportion of cases detected by CDPHS. RESULTS: In total, 1.77 million people, 24% of the Hong Kong population, participated in the UCTP from 1 to 14 September 2020. The UCTP identified 32 new infections (1.8 per 100000 samples tested), consisting of 29% of all local cases reported during the two-week UCTP period. Compared with the CDPHS, the UCTP detected a higher proportion of sporadic cases (62% vs 27%, P<.01) and identified 6 (out of 18) additional clusters during that period. We estimated that 27% (95% credible interval: 22%, 34%) of all infections were detected by the CDPHS in the third wave. CONCLUSIONS: We reported empirical evidence of the utility of population-wide COVID-19 testing in detecting unrecognized infections and clusters. Around three quarters of infections have not been identified through existing surveillance approaches including contact tracing.