Daily use of lateral flow devices by contacts of confirmed COVID-19 cases to enable exemption from isolation compared with standard self-isolation to reduce onward transmission of SARS-CoV-2 in England: a randomised, controlled, non-inferiority trial.

BACKGROUND: In the UK, during the study period (April to July, 2021), all contacts of people with COVID-19 were required to self-isolate for 10 days, which had adverse impacts on individuals and society. Avoiding the need to self-isolate for those who remain uninfected would be beneficial. We investigated whether daily use of lateral flow devices (LFDs) to test for SARS-CoV-2, with removal of self-isolation for 24 h if negative, could be a safe alternative to self-isolation as a means to minimise onward transmission of the virus. METHODS: We conducted a randomised, controlled, non-inferiority trial in adult contacts identified by COVID-19 contact tracing in England. Consenting participants were randomly assigned to self-isolation (single PCR test, 10-day isolation) or daily contact testing (DCT; seven LFD tests, two PCR tests, no isolation if negative on LFD); participants from a single household were assigned to the same group. Participants were prospectively followed up, with the effect of each intervention on onward transmission established from routinely collected NHS Test and Trace contact tracing data for participants who tested PCR-positive for SARS-CoV-2 during the study period and tertiary cases arising from their contacts (ie, secondary contacts). The primary outcome of the study was the attack rate, the percentage of secondary contacts (close contacts of SARS-CoV-2-positive study participants) who became COVID-19 cases (tertiary cases) in each group. Attack rates were derived from Bernoulli regression models using Huber-White (robust) sandwich estimator clustered standard errors. Attack rates were adjusted for household exposure, vaccination status, and ability to work from home. The non-inferiority margin was 1·9%. The primary analysis was a modified intention-to-treat analysis excluding those who actively withdrew from the study as data from these participants were no longer held. This study is registered with the Research Registry (number 6809). Data collection is complete; analysis is ongoing. FINDINGS: Between April 29 and July 28, 2021, 54 923 eligible individuals were enrolled in the study, with final group allocations (following withdrawals) of 26 123 (52·6%) participants in the DCT group and 23 500 (47·4%) in the self-isolation group. Overall, 4694 participants tested positive for SARS-CoV-2 by PCR (secondary cases), 2364 (10·1%) in the self-isolation group and 2330 (8·9%) in the DCT group. Adjusted attack rates (among secondary contacts) were 7·5% in the self-isolation group and 6·3% in the DCT group (difference of -1·2% [95% CI -2·3 to -0·2]; significantly lower than the non-inferiority margin of 1·9%). INTERPRETATION: DCT with 24 h exemption from self-isolation for essential activities appears to be non-inferior to self-isolation. This study, which provided evidence for the UK Government's daily lateral flow testing policy for vaccinated contacts of COVID-19 cases, indicated that daily testing with LFDs could allow individuals to reduce the risk of onward transmission while minimising the adverse effects of self-isolation. Although contacts in England are no longer required to isolate, the findings will be relevant for future policy decisions around COVID-19 or other communicable infections. FUNDING: UK Government Department of Health and Social Care.

Determining Temperature Preference of Mosquitoes and Other Ectotherms.

Most insects and other ectotherms have a relatively narrow optimal temperature window, and deviation from their optima can have significant effects on their fitness, as well as other characteristics. Consequently, many such ectotherms seek out their optimal temperature range. Although temperature preferences of mosquitoes and other insects have been well studied, the traditional experimental setup is performed using a temperature gradient on an aluminum surface in a highly enclosed space. In some cases, this equipment restricts many natural behaviors, such as flying, which may be important in preference selection. The objective of this study is to observe insect preference for air temperature by using a two-chamber apparatus with sufficient room for flight. The two chambers consist of independent temperature-controlled incubators, each with a large aperture. The incubators are connected by these apertures using a short acrylic bridge. Inside the incubators are two netted cages, linked via the apertures and bridge, allowing the insects to freely fly between the different conditions. The acrylic bridge also acts as a temperature gradient between the two incubators. Due to the spacious area in the cage and easy construction, this method can be used to study any small ectotherm and/or any manipulation which may alter temperature preference including sensory organ manipulation, diet, gut flora, and endosymbiont presence at biosafety levels 1 or 2 (BSL 1 or 2). Additionally, the apparatus can be used for the study of pathogen infection using further containment (e.g., inside of a biosafety cabinet) at BSL 3.

Enhancing epidemiological surveillance of the emergence of the SARS-CoV-2 Omicron variant using spike gene target failure data, England, 15 November to 31 December 2021.

When SARS-CoV-2 Omicron emerged in 2021, S gene target failure enabled differentiation between Omicron and the dominant Delta variant. In England, where S gene target surveillance (SGTS) was already established, this led to rapid identification (within ca 3 days of sample collection) of possible Omicron cases, alongside real-time surveillance and modelling of Omicron growth. SGTS was key to public health action (including case identification and incident management), and we share applied insights on how and when to use SGTS.

Assessing the suitability for Aedes albopictus and dengue transmission risk in China with a delay differential equation model.

Dengue is considered non-endemic to mainland China. However, travellers frequently import the virus from overseas and local mosquito species can then spread the disease in the population. As a consequence, mainland China still experiences large dengue outbreaks. Temperature plays a key role in these outbreaks: it affects the development and survival of the vector and the replication rate of the virus. To better understand its implication in the transmission risk of dengue, we developed a delay differential equation model that explicitly simulates temperature-dependent development periods and tested it with collected field data for the Asian tiger mosquito, Aedes albopictus. The model predicts mosquito occurrence locations with a high accuracy (Cohen's κ of 0.78) and realistically replicates mosquito population dynamics. Analysing the infection dynamics during the 2014 dengue outbreak that occurred in Guangzhou showed that the outbreak could have lasted for another four weeks if mosquito control interventions had not been undertaken. Finally, we analyse the dengue transmission risk in mainland China. We find that southern China, including Guangzhou, can have more than seven months of dengue transmission per year while even Beijing, in the temperate north, can have dengue transmission during hot summer months. The results demonstrate the importance of using detailed vector and infection ecology, especially when vector-borne disease transmission risk is modelled over a broad range of climatic zones.

Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide.

Approximately a year into the COVID-19 pandemic caused by the SARS-CoV-2 virus, many countries have seen additional "waves" of infections, especially in the temperate northern hemisphere. Other vulnerable regions, such as South Africa and several parts of South America have also seen cases rise, further impacting local economies and livelihoods. Despite substantial research efforts to date, it remains unresolved as to whether COVID-19 transmission has the same sensitivity to climate observed for other common respiratory viruses such as seasonal influenza. Here, we look for empirical evidence of seasonality using a robust estimation framework. For 359 large cities across the world, we estimated the basic reproduction number (R0) using logistic growth curves fitted to cumulative case data. We then assess evidence for association with climatic variables through ordinary least squares (OLS) regression. We find evidence of seasonality, with lower R0 within cities experiencing greater surface radiation (coefficient = -0.005, p < 0.001), after adjusting for city-level variation in demographic and disease control factors. Additionally, we find association between R0 and temperature during the early phase of the epidemic in China. However, climatic variables had much weaker explanatory power compared to socioeconomic and disease control factors. Rates of transmission and health burden of the continuing pandemic will be ultimately determined by population factors and disease control policies.

Spatiotemporal dynamics of hemorrhagic fever with renal syndrome in Jiangxi province, China.

Historically, Jiangxi province has had the largest HFRS burden in China. However, thus far, the comprehensive understanding of the spatiotemporal distributions of HFRS is limited in Jiangxi. In this study, seasonal decomposition analysis, spatial autocorrelation analysis, and space-time scan statistic analyses were performed to detect the spatiotemporal dynamics distribution of HFRS cases from 2005 to 2018 in Jiangxi at the county scale. The epidemic of HFRS showed the characteristic of bi-peak seasonality, the primary peak in winter (November to January) and the second peak in early summer (May to June), and the amplitude and the magnitude of HFRS outbreaks have been increasing. The results of global and local spatial autocorrelation analysis showed that the HFRS epidemic exhibited the characteristic of highly spatially heterogeneous, and Anyi, Fengxin, Yifeng, Shanggao, Jing'an and Gao'an county were hot spots areas. A most likely cluster, and two secondary likely clusters were detected in 14-years duration. The higher risk areas of the HFRS outbreak were mainly located in Jiangxi northern hilly state, spreading to Wuyi mountain hilly state as time advanced. This study provided valuable information for local public health authorities to design and implement effective measures for the control and prevention of HFRS.

Evolutionary stability of plant-pollinator networks: efficient communities and a pollination dilemma.

Mutualistic interactions between species are ubiquitous in nature and essential for ecosystem functioning. Often dozens or even hundreds of species with different degrees of specialisation form complex networks. How this complexity evolves is a fundamental question in ecology. Here, we present a new game theoretical approach to model complex coevolutionary processes and apply it to pollination networks. A theoretical analysis reveals multiple evolutionary stable network structures that depend on the availability of pollination service. In particular, we find efficient communities, in which a high percentage of pollen are transported conspecifically, to evolve only when plant and pollinator abundances are well balanced. Both pollinator shortage and oversupply select for more inefficient network structures. The results suggest that availability of pollination services is a key factor structuring pollination networks and may offer a new explanation for geographical differences in pollination communities that have long been recognised by ecologists.

Potential for Zika virus transmission by mosquitoes in temperate climates.

Mosquito-borne Zika virus (ZIKV) transmission has almost exclusively been detected in the tropics despite the distributions of its primary vectors extending farther into temperate regions. Therefore, it is unknown whether ZIKV's range has reached a temperature-dependent limit, or if it can spread into temperate climates. Using field-collected mosquitoes for biological relevance, we found that two common temperate mosquito species, Aedes albopictus and Ochlerotatus detritus, were competent for ZIKV. We orally exposed mosquitoes to ZIKV and held them at between 17 and 31°C, estimated the time required for mosquitoes to become infectious, and applied these data to a ZIKV spatial risk model. We identified a minimum temperature threshold for the transmission of ZIKV by mosquitoes between 17 and 19°C. Using these data, we generated standardized basic reproduction number R0-based risk maps and we derived estimates for the length of the transmission season for recent and future climate conditions. Our standardized R0-based risk maps show potential risk of ZIKV transmission beyond the current observed range in southern USA, southern China and southern European countries. Transmission risk is simulated to increase over southern and Eastern Europe, northern USA and temperate regions of Asia (northern China, southern Japan) in future climate scenarios.

Global risk model for vector-borne transmission of Zika virus reveals the role of El Niño 2015.

Zika, a mosquito-borne viral disease that emerged in South America in 2015, was declared a Public Health Emergency of International Concern by the WHO in February of 2016. We developed a climate-driven R0 mathematical model for the transmission risk of Zika virus (ZIKV) that explicitly includes two key mosquito vector species: Aedes aegypti and Aedes albopictus The model was parameterized and calibrated using the most up to date information from the available literature. It was then driven by observed gridded temperature and rainfall datasets for the period 1950-2015. We find that the transmission risk in South America in 2015 was the highest since 1950. This maximum is related to favoring temperature conditions that caused the simulated biting rates to be largest and mosquito mortality rates and extrinsic incubation periods to be smallest in 2015. This event followed the suspected introduction of ZIKV in Brazil in 2013. The ZIKV outbreak in Latin America has very likely been fueled by the 2015-2016 El Niño climate phenomenon affecting the region. The highest transmission risk globally is in South America and tropical countries where Ae. aegypti is abundant. Transmission risk is strongly seasonal in temperate regions where Ae. albopictus is present, with significant risk of ZIKV transmission in the southeastern states of the United States, in southern China, and to a lesser extent, over southern Europe during the boreal summer season.

Geographical variation in the heterogeneity of mutualistic networks.

Plant-animal mutualistic networks are characterized by highly heterogeneous degree distributions. The majority of species interact with few partner species, while a small number are highly connected to form network hubs that are proposed to play an important role in community stability. It has not been investigated, however, if or how the degree distributions vary among types of mutualisms or communities, or between plants and animals in the same network. Here, we evaluate the degree distributions of pollination and seed-dispersal networks, which are two major types of mutualistic networks that have often been discussed in parallel, using an index based on Pielou's evenness. Among 56 pollination networks we found strong negative correlation of the heterogeneity between plants and animals, and geographical shifts of network hubs from plants in temperate regions to animals in the tropics. For 28 seed-dispersal networks, by contrast, the correlation was positive, and there is no comparable geographical pattern. These results may be explained by evolution towards specialization in the presence of context-dependent costs that occur if plants share the animal species as interaction partner. How the identity of network hubs affects the stability and resilience of the community is an important question for future studies.