Context-specific emergence and growth of the SARS-CoV-2 Delta variant

Patch models can better reflect the impact of spatial heterogeneity and population mobility on disease transmission. While, there is relatively little work on using patch models to study the role of travel restrictions, contact tracing and vaccination in COVID-19 epidemic. In this paper, based on COVID-19 epidemic propagation and diffusion mechanism, we establish a dynamic model of disease spread among two patches in which Wuhan is regarded as one patch and the rest of Mainland China (outside Wuhan) as the other patch. The existence of the final size is proved theoretically and some model parameters are estimated by using the reported confirmed cases. The results show that travel restrictions greatly reduce the number of confirmed cases in Mainland China, and the earlier enforced, the fewer confirmed cases. However, it is impossible to bring the COVID-19 epidemic under control and lift travel restrictions on April 8, 2020 by imposing travel restrictions alone, the same is true for contact tracing. While, the disease can always be controlled if the protection rate of herd immunity is high enough and the corresponding critical threshold is given. Therefore, in order to quickly control the spread of the emerging infectious disease (such as COVID-19), it is necessary to combine a variety of control measures and develop vaccines and therapeutic drugs as soon as possible.

Non-pharmaceutical interventions (NPIs) are central to mitigating COVID-19 and influenza, yet comparative economic evaluations remain scarce. This systematic review assessed the cost effectiveness and reporting quality of NPI evaluations across both diseases. The study was registered with PROSPERO (CRD42024552613). Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, we searched five medical (PubMed, Scopus, EMBASE, CINAHL, and EconLit) and four health technology assessment databases (NHS HTA, CRD DARE, NHS EED, and INAHTA) up to December 2025, including only full economic evaluations. The search strategy incorporated four domains-'influenza,' 'COVID-19,' 'NPIs,' and 'economic evaluation'-and was guided by the WHO NPI framework, encompassing five domains: personal protective, environmental, physical distancing, travel-related, and educational measures. Reporting quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) checklist. Thirty-three studies (13 influenza, 20 COVID-19), predominantly from high-income countries, were included. School closures, the most frequently evaluated NPI, were generally not cost effective except during severe pandemics or bundled with other measures. Workforce and business closures were cost effective only in high-severity influenza, with inconsistent findings for COVID-19. Social distancing was cost effective for COVID-19 but not for H1N1 influenza. Isolation, lockdowns, and travel restrictions were cost effective only when implemented early. Face masks and hand hygiene, assessed solely for COVID-19, were generally cost effective when implemented alongside other measures. The median CHEERS score was 75.0%, with one study rated excellent. Our review highlights heterogeneity in cost effectiveness by pandemic severity, intervention type, bundling of measures, and timing. Strategies that combined low-cost NPIs like masks or hand hygiene demonstrated better value, while socially disruptive measures like school and business closure incurred high costs with inconsistent cost-effectiveness outcomes. Integration with vaccines or antivirals further enhanced cost effectiveness. Evidence gaps include the scarcity of evaluations from low-resource settings and variability in country-specific value thresholds. Addressing these gaps is essential for guiding efficient and cost-effective pandemic preparedness.

International travel–related nonpharmaceutical interventions (NPIs), which can include traveler screening, travel restrictions, and border closures, often are included in national influenza pandemic preparedness plans. We performed systematic reviews to identify evidence for their effectiveness. We found 15 studies in total. Some studies reported that NPIs could delay the introduction of influenza virus. However, no available evidence indicated that screening of inbound travelers would have a substantial effect on preventing spread of pandemic influenza, and no studies examining exit screening were found. Some studies reported that travel restrictions could delay the start of local transmission and slow international spread, and 1 study indicated that small Pacific islands were able to prevent importation of pandemic influenza during 1918–19 through complete border closure. This limited evidence base indicates that international travel-related NPIs would have limited effectiveness in controlling pandemic influenza and that these measures require considerable resources to implement.

BackgroundIn an influenza pandemic, the benefit of vaccines and antiviral medications will be constrained by limitations on supplies and effectiveness. Non-pharmaceutical public health interventions will therefore be vital in curtailing disease spread. However, the most comprehensive assessments of the literature to date recognize the generally poor quality of evidence on which to base non-pharmaceutical pandemic planning decisions. In light of the need to prepare for a possible pandemic despite concerns about the poor quality of the literature, combining available evidence with expert opinion about the relative merits of non-pharmaceutical interventions for pandemic influenza may lead to a more informed and widely accepted set of recommendations. We evaluated the evidence base for non-pharmaceutical public health interventions. Then, based on the collective evidence, we identified a set of recommendations for and against interventions that are specific to both the setting in which an intervention may be used and the pandemic phase, and which can be used by policymakers to prepare for a pandemic until scientific evidence can definitively respond to planners' needs.MethodsBuilding on reviews of past pandemics and recent historical inquiries, we evaluated the relative merits of non-pharmaceutical interventions by combining available evidence from the literature with qualitative and quantitative expert opinion. Specifically, we reviewed the recent scientific literature regarding the prevention of human-to-human transmission of pandemic influenza, convened a meeting of experts from multiple disciplines, and elicited expert recommendation about the use of non-pharmaceutical public health interventions in a variety of settings (healthcare facilities; community-based institutions; private households) and pandemic phases (no pandemic; no US pandemic; early localized US pandemic; advanced US pandemic).ResultsThe literature contained a dearth of evidence on the efficacy or effectiveness of most non-pharmaceutical interventions for influenza. In an effort to inform decision-making in the absence of strong scientific evidence, the experts ultimately endorsed hand hygiene and respiratory etiquette, surveillance and case reporting, and rapid viral diagnosis in all settings and during all pandemic phases. They also encouraged patient and provider use of masks and other personal protective equipment as well as voluntary self-isolation of patients during all pandemic phases. Other non-pharmaceutical interventions including mask-use and other personal protective equipment for the general public, school and workplace closures early in an epidemic, and mandatory travel restrictions were rejected as likely to be ineffective, infeasible, or unacceptable to the public.ConclusionThe demand for scientific evidence on non-pharmaceutical public health interventions for influenza is pervasive, and present policy recommendations must rely heavily on expert judgment. In the absence of a definitive science base, our assessment of the evidence identified areas for further investigation as well as non-pharmaceutical public health interventions that experts believe are likely to be beneficial, feasible and widely acceptable in an influenza pandemic.

The Coronavirus Response in India – World's Largest Lockdown

On New Zealand's weak, strong and muddled management of a COVID-19 epidemic.

Governments of the world have invested a lot of manpower and material resources to combat COVID-19 this year. At this moment, the most efficient way that could stop the epidemic is to leverage the contact tracing system to monitor people’s daily contact information and isolate the close contacts of COVID-19. However, the contact tracing data usually contains people’s sensitive information that they do not want to share with the contact tracing system and government. Conversely, the contact tracing system could perform better when it obtains more detailed contact tracing data. In this article, we treat the process of collecting contact tracing data from a crowdsourcing perspective in order to motivate users to contribute more contact tracing data and propose the incentive algorithm named CovidCrowd. Different from previous works where they ask users to contribute their data voluntarily, the government offers some reward to users who upload their contact tracing data to reimburse the privacy and data processing cost. We formulate the problem as a Stackelberg game and show there exists a Nash equilibrium for any user given the fixed reward value. Then, CovidCrowd computes the optimal reward value which could maximize the utility of the system. Finally, we conduct a large-scale simulation with thousands of users and evaluation with real-world data set. Both results show that CovidCrowd outperforms the benchmarks, e.g., the user participating level is improved by at least 13.2% for all evaluation scenarios.

The world is experiencing an ongoing pandemic of coronavirus disease-2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In attempts to control the pandemic, a range of nonpharmaceutical interventions (NPIs) has been implemented worldwide. However, the effect of synchronized NPIs for the control of COVID-19 at temporal and spatial scales has not been well studied. Therefore, a meta-population model that incorporates essential nonlinear processes was constructed to uncover the transmission characteristics of SARS-CoV-2 and then assess the effectiveness of synchronized NPIs on COVID-19 dynamics in China. Regional synchronization of NPIs was observed in China, and it was found that a combination of synchronized NPIs (the travel restrictions, the social distancing and the infection isolation) prevented 93.7% of SARS-CoV-2 infections. The use of synchronized NPIs at the time of the Wuhan lockdown may have prevented as much as 38% of SARS-CoV-2 infections, compared with the unsynchronized scenario. The interconnectivity of the epicenter, the implementation time of synchronized NPIs, and the number of regions considered all affected the performance of synchronized NPIs. The results highlight the importance of using synchronized NPIs in high-risk regions for the control of COVID-19 and shed light on effective strategies for future pandemic responses.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11071-021-06505-0.

Introduction:Contact tracing is a core public health tool used to interrupt the transmission of pathogens, including SARS-CoV-2. To increase the effectiveness of contact tracing, Greek health authorities used an electronic platform to aid traditional manual contact tracing to track individuals who have come in close contact with identified COVID-19 patients.Method:Contact tracing was implemented from the beginning of the pandemic in Greece. The aim was to identify and quarantine all the contacts of confirmed cases. The electronic database was designed following all the security protocols and national regulations on the use and protection of personal data. To assess factors associated with infectivity and susceptibility to infection in this analysis, we used contact tracing data with a sampling date between October 1 to December 9, 2020.Results:During the sampling period, 29,385 laboratory-confirmed SARS-CoV-2 cases and 64,608 traced contacts were identified. A median number of two persons were traced per index case. The secondary attack rate was 17.4% (95% CI: 17.0-17.8). Contacts aged 0–11 and 12–17 years were less susceptible to infection than adults 65 years or older (odds ratio (OR) [95% CI]: 0.28 [0.26–0.32] and 0.44 [0.40–0.49], respectively). Index cases aged 65 years or older were more likely to infect their contacts than other adults or children/adolescents.Conclusion:Contact tracing is a key strategy to interrupt chains of transmission and to promote early diagnosis. The data collected in this process could be used to estimate epidemiological parameters of interest and to better understand factors associated with infection and susceptibility to infection. Precautions are necessary for individuals 65 or older as they have higher infectivity and susceptibility in contact with their peers.

In mid-November, 2021, the SARS-CoV-2 omicron variant (B.1.1.529; BA.1 sublineage) was detected in southern Africa, prompting international travel restrictions. We aimed to investigate the spread of omicron BA.1 in Africa. In this observational study, samples from patients infected with SARS-CoV-2 from 27 laboratories in 24 African countries, collected between June 1, 2021 and April 14, 2022, were tested for omicron BA.1 and delta (B.1.617.2) variants using real-time RT-PCR. Samples that tested positive for BA.1 by RT-PCR and were collected before estimated BA.1 emergence according to epidemiological properties were excluded from downstream analyses. The diagnostic precision of the assays was evaluated by high-throughput sequencing of samples from four countries. The observed spread of BA.1 was compared with mobility-based mathematical simulations and entries for SARS-CoV-2 in the Global Initiative on Sharing All Influenza Data (GISAID) genomic database. We estimated the effective reproduction number (Rt) at the country level considering the BA.1 fraction and the reported numbers of infections. Phylogeographical analyses were done in a Bayesian framework. Through testing of 13 294 samples from patients infected with SARS-CoV-2, we established that, by November-December, 2021, omicron BA.1 had replaced the delta variant of SARS-CoV-2 in all African subregions, following a south-north gradient, with a median Rt of 2·60 (95% CI 2·46-2·71). This south-north spread, established on the basis of PCR data, was substantiated by phylogeographical reconstructions, ancestral state reconstructions, and GISAID data. PCR-based reconstructions of country-level BA.1 predominance and the availability of BA.1 genomic sequences in GISAID correlated significantly in time (p=0·0002, r=0·78). The first detections of BA.1 in high-income settings beyond Africa were predicted accurately in time by mobility-based mathematical simulations (p<0·0001). Comparing PCR-based reconstructions with mobility-based mathematical simulations suggested that SARS-CoV-2 infections in Africa were under-reported by approximately ten times. Inbound travellers infected with BA.1, departing from five continents, were identified in six African countries by early December, 2021. Omicron BA.1 was widespread in Africa when travel bans were implemented, limiting their effectiveness. Combined with genomic surveillance and mobility-based mathematical modelling, PCR-based strategies can inform Rt and the geographical spread of emerging pathogens in a cost-effective and timely manner, and can guide evidence-based, non-pharmaceutical interventions such as travel restrictions or physical distancing. Bill & Melinda Gates Foundation. For the French, Portugese and Spanish translations of the abstract see Supplementary Materials section.

During the COVID-19 pandemic, some countries, such as Australia, China, Iceland, New Zealand, Thailand, and Vietnam successfully implemented an elimination strategy, enacting strict border control and periods of lockdowns to end community transmission. Atlantic Canada and Canada’s territories implemented similar policies, and reported long periods with no community cases. In Newfoundland and Labrador (NL), Nova Scotia, and Prince Edward Island a median of 80% or more of daily reported cases were travel-related from July 1, 2020 to May 31, 2021. With increasing vaccination coverage, it may be appropriate to exit an elimination strategy, but most existing epidemiological frameworks are applicable only to situations where most cases occur in the community, and are not appropriate for regions that have implemented an elimination strategy. To inform the pandemic response in regions that are implementing an elimination strategy, we extend importation modelling to consider post-arrival travel restrictions, and pharmaceutical and non-pharmaceutical interventions in the local community. We find that shortly after the Omicron variant had begun spreading in Canada, the expected daily number of spillovers, infections spread to NL community members from travellers and their close contacts, was higher than any time previously in the pandemic. By December 24, 2021, the expected number of spillovers was 44% higher than the previous high, which occurred in late July 2021 shortly after travel restrictions were first relaxed. We develop a method to assess the characteristics of potential future community outbreaks in regions that are implementing an elimination strategy. We apply this method to predict the effect of variant and vaccination coverage on the size of hypothetical community outbreaks in Mount Pearl, a suburb of the St. John’s metropolitan area in NL. Our methodology can be used to evaluate alternative plans to relax public health restrictions when vaccine coverage is high in regions that have implemented an elimination strategy. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.

Human mobility, contact patterns, and their interplay are key aspects of our social behavior that shape the spread of infectious diseases across different regions. In the light of new evidence and data sets about these two elements, epidemic models should be refined to incorporate both the heterogeneity of human contacts and the complexity of mobility patterns. Here, we propose a theoretical framework that allows accommodating these two aspects in the form of a set of Markovian equations. We validate these equations with extensive mechanistic simulations and derive analytically the epidemic threshold. The expression of this critical value allows us to evaluate its dependence on the specific demographic distribution, the structure of mobility flows, and the heterogeneity of contact patterns, thus shedding light on the microscopic mechanisms responsible for the epidemic detriment driven by recurrent mobility patterns reported in the literature.

Heterogeneity in contact patterns, mortality rates, and transmissibility among and between different age classes can have significant effects on epidemic outcomes. Adaptive behavior in response to the spread of an infectious pathogen may give rise to complex epidemiological dynamics. Here we model an infectious disease in which adaptive behavior incentives, and mortality rates, can vary between two and three age classes. The model indicates that age-dependent variability in infection aversion can produce more complex epidemic dynamics at lower levels of pathogen transmissibility and that those at less risk of infection can still drive complexity in the dynamics of those at higher risk of infection. Policymakers should consider the interdependence of such heterogeneous groups when making decisions.

The social fine structure of a population plays a central role in ecological and evolutionary processes. Whilst many studies have investigated how morphological traits such as size affect social structure of populations, comparatively little is known about the influence of behaviours such as boldness and shyness. Using information on social interactions in a wild population of Trinidadian guppies (Poecilia reticulata), we construct a social network. For each individual in the network, we quantify its behavioural phenotype using two measures of boldness, predator inspection tendency, a repeatable and reliably measured behaviour well studied in the context of co-operation, and shoaling tendency. We observe striking heterogeneity in contact patterns, with strong ties being positively assorted and weak ties negatively assorted by our measured behavioural traits. Moreover, shy fish had more network connections than bold fish and these were on average stronger. In other words, social fine structure is strongly influenced by behavioural trait. We assert that such structure will have implications for the outcome of selection on behavioural traits and we speculate that the observed positive assortment may act as an amplifier of selection contributing to the maintenance of co-operation during predator inspection.

By 15 February, the UK had given first doses of covid-19 vaccine to more than 15 million people. It explicitly prioritised old, frail, and sick people because of their higher...