Routes of importation and spatial dynamics of SARS-CoV-2 variants during localised interventions in Chile (preprint)

South America suffered large SARS-CoV-2 epidemics between 2020 and 2022 caused by multiple variants of interest and concern, some causing substantial morbidity and mortality. However, their transmission dynamics are poorly characterised. The epidemic situation in Chile enables us to investigate differences in the distribution and spread of variants Alpha, Gamma, Lambda, Mu and Delta. Chile implemented non-pharmaceutical interventions and an integrated genomic and epidemiological surveillance system that included airport and community surveillance to track SARS-CoV-2 variants. Here we combine viral genomic data and anonymised human mobility data from mobile phones to characterise the routes of importation of different variants into Chile, the relative contributions of airport-based importations to viral diversity versus land border crossings and test the impact of the mobility network on the diffusion of viral lineages within the country. We find that Alpha, Lambda and Mu were identified in Chile via airport surveillance six, four and five weeks ahead of their detection via community surveillance, respectively. Further, some variants that originated in South America were imported into Chile via land rather than international air travel, most notably Gamma. Different variants exhibited similar trends of viral dissemination throughout the country following their importation, and we show that the mobility network predicts the time of arrival of imported lineages to different Chilean comunas. Higher stringency of local NPIs was also associated with fewer domestic viral importations. Our results show how genomic surveillance combined with high resolution mobility data can help predict the multi-scale geographic expansion of emerging infectious diseases. Significance statementGlobal preparedness for pandemic threats requires an understanding of the global variations of spatiotemporal transmission dynamics. Regional differences are important because the local context sets the conditions for the unfolding of local epidemics, which in turn affect transmission dynamics at a broader scale. Knowledge gaps from the SARS-CoV-2 pandemic remain for regions like South America, where distinct sets of viral variants emerged and spread from late 2020 onwards, and where changes in human behaviour resulted in epidemics which differed from those observed in other regions. Our interdisciplinary analysis of the SARS-CoV-2 epidemic in Chile provides insights into the spatiotemporal trends of viral diffusion in the region which shed light on the drivers that can influence future epidemic waves and pandemics.

COVID-19 pandemic re-shaped the global dispersal of seasonal influenza viruses (preprint)

Understanding how the global dispersal patterns of seasonal influenza viruses were perturbed during and after the COVID-19 pandemic is needed to inform influenza intervention and vaccination strategies in the post-pandemic period. Although global human mobility has been identified as a key driver of influenza dispersal1, alongside climatic and evolutionary factors2,3, the impact of international travel restrictions on global influenza transmission and recovery remains unknown. Here we combine molecular, epidemiological, climatic, and international travel data within a phylodynamic framework to show that, despite human mobility remaining the principal driver of global influenza virus dissemination, the pandemics onset led to a shift in the international population structure and migration network of seasonal influenza lineages. We find that South Asia and Africa played important roles as exporters and phylogenetic trunk locations of influenza in 2020 and 2021, and we highlight the association between population movement, antigenic drift and persistence during the intensive non-pharmaceutical interventions (NPIs) phase. The influenza B/Yamagata lineage disappeared in a context of reduced relative genetic diversity, moderate lineage turnover, and lower positive selection pressure. Our results demonstrate that mobility perturbations reshaped the global dispersal dynamics of influenza viruses, with potential implications for vaccine design and genomic surveillance programmes. As the risk of future pandemics persists, our study provides an opportunity to assess the impact of NPIs during the pandemic on respiratory infectious diseases beyond the interplay between SARS-CoV-2 and influenza viruses.

Understanding COVID-19 testing behaviour in England through a sociodemographic lens (preprint)

BackgroundUnderstanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour can help to protect the vulnerable and guide equity-driven interventions. Using COVID-19 testing data for England and data from community prevalence surveillance surveys (REACT-1 and ONS-CIS) from October 2020 to March 2022, we investigated the relationship between sociodemographic factors and testing behaviours in England. MethodsWe used mass testing data for lateral flow device (LFD; data for 290 million tests performed and reported) and polymerase chain reaction (PCR) (data for 107 million tests performed and returned from the laboratory) tests made available for the general public, provided by date, self-reported age and ethnicity at lower tier local authority (LTLA) level. Using a mechanistic causal model to debias the PCR testing data, we obtained estimates of weekly SARS-CoV-2 prevalence by self-reported ethnic groups and age groups for LTLAs in England. This approach to debiasing the PCR (or LFD) testing data also estimated a testing bias parameter defined as the odds of testing in infected versus not infected individuals, which would be close to zero if the likelihood of test seeking (or seeking and reporting) was the same regardless of infection status. Using confirmatory PCR data, we estimated false positivity rates, sensitivity, specificity, and the rate of decline in detection probability by PCR by sociodemographic groups. We also estimated the daily incidence allowing us to determine the fraction of cases captured by the testing programme. FindingsFrom March 2021 onwards, individuals in the most deprived regions reported approximately half as many LFD tests per-capita than those in the least deprived areas (Median ratio [Inter quartile range, IQR]: 0{middle dot}50 [0{middle dot}44, 0{middle dot}54]). During October 2020 - June 2021, PCR testing patterns were in the opposite direction (Median ratio [IQR]: 1{middle dot}8 [1{middle dot}7, 1{middle dot}9]). Infection prevalences in Asian or Asian British communities were considerably higher than those of other ethnic groups during the Alpha and Omicron BA.1 waves. Our estimates indicate that the England COVID-19 testing program detected 26% - 40% of all cases (including asymptomatic cases) over the study period with no consistent differences by deprivation levels or ethnic groups. PCR testing biases were generally higher than for LFDs, which was in line with the general policy of symptomatic and asymptomatic use of these tests. During the invasion phases of the Delta and Omicron variants of concern, the PCR testing bias in the most deprived populations was roughly double (ratio: 2{middle dot}2 and 2{middle dot}7 respectively) that in the least. We also determined that ethnic minorities and older individuals were less likely to use confirmatory PCR tests through most of the pandemic and that there was possibly a longer delay in reporting a positive LFD test in the Black populations. InterpretationDifferences in testing behaviours across sociodemographic groups may be reflective of the relatively higher costs of self-isolation to vulnerable populations, differences in test accessibility, digital literacy, and differing perception about the utility of tests and risks posed by infection. Our work shows how mass testing data can be used in conjunction with surveillance surveys to identify gaps in the uptake of public health interventions at fine scale levels and by sociodemographic groups. It provides a framework for monitoring local interventions and yields valuable lessons for policy makers in ensuring an equitable response to future pandemics. FundingUK Health Security Agency.

Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha (preprint)

SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Understanding the drivers of such silent spread and its epidemic impact is critical to inform future response planning. Here, we integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the early dissemination of Alpha out of the UK in the first three months after emergence. We found that silent circulation lasted from days to months and was logarithmically associated with sequencing coverage. Social restrictions in certain countries likely slowed down the seeding of local transmission by weeks, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.

Spatial scales of COVID-19 transmission in Mexico (preprint)

During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing non-pharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases, deaths and hospitalizations at the municipality level in Mexico to investigate how behavioural changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March - June 2020). We find that the epidemic dynamics in Mexico were initially driven by SARS-CoV-2 exports from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronised. Our results provide actionable and dynamic insights into how to use network science and epidemiological modelling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general.

Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1 (preprint)

SARS-CoV-2 variants of concern (VOCs) arise against the backdrop of increasingly heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron genomes, we identified >6,000 independent introductions of the antigenically distinct virus into England and reconstructed the dispersal history of resulting local transmission. Travel restrictions on southern Africa did not reduce BA.1 importation intensity as secondary hubs became major exporters. We explored potential drivers of BA.1 spread across England and discovered an early period during which viral lineage movements mainly occurred between larger cities, followed by a multi-focal spatial expansion shaped by shorter distance mobility patterns. We also found evidence that disease incidence impacted human commuting behaviours around major travel hubs. Our results offer a detailed characterisation of processes that drive the invasion of an emerging VOC across multiple spatial scales and provide unique insights on the interplay between disease spread and human mobility.

Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic (preprint)

The COVID-19 pandemic offers an unprecedented natural experiment providing insights into the emergence of collective behavioral changes of both exogenous (government mandated) and endogenous (spontaneous reaction to infection risks) origin. Here, we characterize collective physical distancing -- mobility reductions, minimization of contacts, shortening of contact duration -- in response to the COVID-19 pandemic in the pre-vaccine era by analyzing de-identified, privacy-preserving location data for a panel of over 5.5 million anonymized, opted-in U.S. devices. We define five indicators of users' mobility and proximity to investigate how the emerging collective behavior deviates from the typical pre-pandemic patterns during the first nine months of the COVID-19 pandemic. We analyze both the dramatic changes due to the government mandated mitigation policies and the more spontaneous societal adaptation into a new (physically distanced) normal in the fall 2020. The indicators defined here allow the quantification of behavior changes across the rural/urban divide and highlight the statistical association of mobility and proximity indicators with metrics characterizing the pandemic's social and public health impact such as unemployment and deaths. This study provides a framework to study massive social distancing phenomena with potential uses in analyzing and monitoring the effects of pandemic mitigation plans at the national and international level.

Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel (preprint)

In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance.

Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico (preprint)

Up to November 2021, over 200 different SARS-CoV-2 lineages circulated in Mexico. To investigate lineage replacement dynamics, we applied a phylodynamic approach to explore the evolutionary trajectories of five dominant lineages that circulated during the first year of the local epidemic. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in the country. Lineages B.1.1.222 and B.1.1.519 showed comparable dynamics, represented by clades likely originating in Mexico and persisting for over a year. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. We further explored viral movements across the country, applied within the largest clades identified (belonging to lineage B.1.617.2). Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.

An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients (preprint)

BackgroundWhilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. MethodsHere, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. ResultsOur analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61 - 0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. ConclusionsAlthough clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.

Forecasting hospital-level COVID-19 admissions using real-time mobility data (preprint)

For each of the COVID-19 pandemic waves, hospitals have had to plan for deploying surge capacity and resources to manage large but transient increases in COVID-19 admissions. While a lot of effort has gone into predicting regional trends in COVID-19 cases and hospitalizations, there are far fewer successful tools for creating accurate hospital-level forecasts. At the same time, anonymized phone-collected mobility data proved to correlate well with the number of cases for the first two waves of the pandemic (spring 2020, and fall-winter 2021). In this work, we show how mobility data could bolster hospital-specific COVID-19 admission forecasts for five hospitals in Massachusetts during the initial COVID-19 surge. The high predictive capability of the model was achieved by combining anonymized, aggregated mobile device data about users' contact patterns, commuting volume, and mobility range with COVID hospitalizations and test-positivity data. We conclude that mobility-informed forecasting models can increase the lead-time of accurate predictions for individual hospitals, giving managers valuable time to strategize how best to allocate resources to manage forthcoming surges.

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

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter- regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador (preprint)

Characterisation of SARS-CoV-2 genetic diversity through space and time can reveal trends in virus importation and domestic circulation, and permit the exploration of questions regarding the early transmission dynamics. Here we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the COVID-19 pandemic. We generate and analyse 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylgeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions (NPIs), with differential degrees of persistence and national dissemination.

Transmission of SARS-CoV-2 before and after symptom onset: impact of nonpharmaceutical interventions in China (preprint)

Nonpharmaceutical interventions, such as contact tracing and quarantine, are currently the primary means of controlling the spread of SARS-CoV-2; however, it remains uncertain which interventions are most effective at reducing transmission at the population level. Using serial interval data from before and after the rollout of nonpharmaceutical interventions in China, we estimate that the relative frequency of presymptomatic transmission increased from 34% before the rollout to 71% afterward. The shift touward earlier transmission indicates a disproportionate reduction in transmission post-symptom onset. We estimate that, following the rollout of nonpharmaceutical interventions, transmission post-symptom onset was reduced by 82% whereas presymptomatic transmission decreased by only 16%. These findings suggest that interventions which limit opportunities for transmission in the later stages of infection, such as contact tracing and isolation, may have been particularly effective at reducing transmission of SARS-CoV-2.

Establishment & lineage dynamics of the SARS-CoV-2 epidemic in the UK (preprint)

The UK's COVID-19 epidemic during early 2020 was one of world's largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown were larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whilst lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Increased travel times to United States SARS-CoV-2 testing sites: a spatial modeling study (preprint)

ImportanceAccess to testing is key to a successful response to the COVID-19 pandemic. ObjectiveTo determine the geographic accessibility to SARS-CoV-2 testing sites in the United States, as quantified by travel time. DesignCross-sectional analysis of SARS-CoV-2 testing sites as of April 7, 2020 in relation to travel time. SettingUnited States COVID-19 pandemic. ParticipantsThe United States, including the 48 contiguous states and the District of Columbia. ExposuresPopulation density, percent minority, percent uninsured, and median income by county from the 2018 American Community Survey demographic data. Main OutcomeSARS-CoV-2 testing sites identified in two national databases (Carbon Health and CodersAgainstCovid), geocoded by address. Median county 1 km2 gridded friction surface of travel times, as a measure of geographic accessibility to SARS-CoV-2 testing sites. Results6,236 unique SARS-CoV-2 testing sites in 3,108 United States counties were identified. Thirty percent of the U.S. population live in a county (N = 1,920) with a median travel time over 20 minutes. This was geographically heterogeneous; 86% of the Mountain division population versus 5% of the Middle Atlantic population lived in counties with median travel times over 20 min. Generalized Linear Models showed population density, percent minority, percent uninsured and median income were predictors of median travel time to testing sites. For example, higher percent uninsured was associated with longer travel time ({beta} = 0.41 min/percent, 95% confidence interval 0.3-0.53, p = 1.2x10-12), adjusting for population density. Conclusions and RelevanceGeographic accessibility to SARS-Cov-2 testing sites is reduced in counties with lower population density and higher percent of minority and uninsured, which are also risk factors for worse healthcare access and outcomes. Geographic barriers to SARS-Cov-2 testing may exacerbate health inequalities and bias county-specific transmission estimates. Geographic accessibility should be considered when planning the location of future testing sites and interpreting epidemiological data. Key PointsO_LISARS-CoV-2 testing sites are distributed unevenly in the US geography and population. C_LIO_LIMedian county-level travel time to SARS-CoV-2 testing sites is longer in less densely populated areas, and in areas with a higher percentage of minority or uninsured populations. C_LIO_LIImproved geographic accessibility to testing sites is imperative to manage the COVID-19 pandemic in the United States. C_LI

Epidemiological and clinical characteristics of the early phase of the COVID-19 epidemic in Brazil (preprint)

BackgroundThe first case of COVID-19 was detected in Brazil on February 25, 2020. We report the epidemiological, demographic, and clinical findings for confirmed COVID-19 cases during the first month of the epidemic in Brazil. MethodsIndividual-level and aggregated COVID-19 data were analysed to investigate demographic profiles, socioeconomic drivers and age-sex structure of COVID-19 tested cases. Basic reproduction numbers (R0) were investigated for Sao Paulo and Rio de Janeiro. Multivariate logistic regression analyses were used to identify symptoms associated with confirmed cases and risk factors associated with hospitalization. Laboratory diagnosis for eight respiratory viruses were obtained for 2,429 cases. FindingsBy March 25, 1,468 confirmed cases were notified in Brazil, of whom 10% (147 of 1,468) were hospitalised. Of the cases acquired locally (77{middle dot}8%), two thirds (66{middle dot}9% of 5,746) were confirmed in private laboratories. Overall, positive association between higher per capita income and COVID-19 diagnosis was identified. The median age of detected cases was 39 years (IQR 30-53). The median R0 was 2{middle dot}9 for Sao Paulo and Rio de Janeiro. Cardiovascular disease/hypertension were associated with hospitalization. Co-circulation of six respiratory viruses, including influenza A and B and human rhinovirus was detected in low levels. InterpretationSocioeconomic disparity determines access to SARS-CoV-2 testing in Brazil. The lower median age of infection and hospitalization compared to other countries is expected due to a younger population structure. Enhanced surveillance of respiratory pathogens across socioeconomic statuses is essential to better understand and halt SARS-CoV-2 transmission. FundingSao Paulo Research Foundation, Medical Research Council, Wellcome Trust and Royal Society.

Risk of COVID-19 is associated with long-term exposure to air pollution (preprint)

High risk of severe disease of COVID-19 has been associated with patients with chronic obstructive pulmonary disease, cardiovascular disease or hypertension, and long-term exposure to PM2.5 has been associated with COVID-19 mortality. We collate individual level data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China by March 6, 2020. We pair these data with a mobile phone dataset, covering human movements from Wuhan before the travel ban and inner-city movements during the time of emergency response from 324 cities in China. Adjusting for socio-economic factors, an increase of 10 g/m3 in NO2 or PM2.5 was found to be associated with a 22.41% (95%CI: 7.28%-39.89%) or 15.35% (95%CI: 5.60%-25.98%) increase in the number of COVID-19 cases, and a 19.20% (95%CI: 4.03%-36.59%) or 9.61% (95%CI: 0.12%-20.01%) increase in severe infection, respectively. Our results highlight the importance of air quality improvements to health benefits.

Crowding and the epidemic intensity of COVID-19 transmission (preprint)

The COVID-19 pandemic is straining public health systems worldwide and major non-pharmaceutical interventions have been implemented to slow its spread. During the initial phase of the outbreak the spread was primarily determined by human mobility. Yet empirical evidence on the effect of key geographic factors on local epidemic spread is lacking. We analyse highly-resolved spatial variables for cities in China together with case count data in order to investigate the role of climate, urbanization, and variation in interventions across China. Here we show that the epidemic intensity of COVID-19 is strongly shaped by crowding, such that epidemics in dense cities are more spread out through time, and denser cities have larger total incidence. Observed differences in epidemic intensity are well captured by a metapopulation model of COVID-19 that explicitly accounts for spatial hierarchies. Densely-populated cities worldwide may experience more prolonged epidemics. Whilst stringent interventions can shorten the time length of these local epidemics, although these may be difficult to implement in many affected settings.

Genomic epidemiology of SARS-CoV-2 in Guangdong Province, China (preprint)

Highlights: 1) 1.6 million molecular diagnostic tests identified 1,388 SARS-CoV-2 infections in Guangdong Province, China, by 19th March 2020; 2) Virus genomes can be recovered using a variety of sequencing approaches from a range of patient samples. 3) Genomic analyses reveal multiple virus importations into Guangdong Province, resulting in genetically distinct clusters that require careful interpretation. 4) Large-scale epidemiological surveillance and intervention measures were effective in interrupting community transmission in Guangdong Summary: COVID-19 is caused by the SARS-CoV-2 coronavirus and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, China's most populous province, during early 2020 resulted in 1,388 reported RNA positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain due to low virus genetic variation early in the pandemic. Our results illustrate how the timing, size and duration of putative local transmission chains were constrained by national travel restrictions and by the province's large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required as the number of cases imported from other countries is increasing.