Ecology of Middle East respiratory syndrome coronavirus, 2012-2020: A machine learning modelling analysis.

The ongoing enzootic circulation of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and North Africa is increasingly raising the concern about the possibility of its recombination with other human-adapted coronaviruses, particularly the pandemic SARS-CoV-2. We aim to provide an updated picture about ecological niches of MERS-CoV and associated socio-environmental drivers. Based on 356 confirmed MERS cases with animal contact reported to the WHO and 63 records of animal infections collected from the literature as of 30 May 2020, we assessed ecological niches of MERS-CoV using an ensemble model integrating three machine learning algorithms. With a high predictive accuracy (area under receiver operating characteristic curve = 91.66% in test data), the ensemble model estimated that ecologically suitable areas span over the Middle East, South Asia and the whole North Africa, much wider than the range of reported locally infected MERS cases and test-positive animal samples. Ecological suitability for MERS-CoV was significantly associated with high levels of bareland coverage (relative contribution = 30.06%), population density (7.28%), average temperature (6.48%) and camel density (6.20%). Future surveillance and intervention programs should target the high-risk populations and regions informed by updated quantitative analyses.

Epidemiology and evolution of Middle East respiratory syndrome coronavirus, 2012-2020.

BACKGROUND: The ongoing transmission of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and its expansion to other regions are raising concerns of a potential pandemic. An in-depth analysis about both population and molecular epidemiology of this pathogen is needed. METHODS: MERS cases reported globally as of June 2020 were collected mainly from World Health Organization official reports, supplemented by other reliable sources. Determinants for case fatality and spatial diffusion of MERS were assessed with Logistic regressions and Cox proportional hazard models, respectively. Phylogenetic and phylogeographic analyses were performed to examine the evolution and migration history of MERS-CoV. RESULTS: A total of 2562 confirmed MERS cases with 150 case clusters were reported with a case fatality rate of 32.7% (95% CI: 30.9‒34.6%). Saudi Arabia accounted for 83.6% of the cases. Age of ≥ 65 years old, underlying conditions and ≥ 5 days delay in diagnosis were independent risk factors for death. However, a history of animal contact was associated with a higher risk (adjusted OR = 2.97, 95% CI: 1.10-7.98) among female cases < 65 years but with a lower risk (adjusted OR = 0.31, 95% CI: 0.18-0.51) among male cases ≥ 65 years old. Diffusion of the disease was fastest from its origin in Saudi Arabia to the east, and was primarily driven by the transportation network. The most recent sub-clade C5.1 (since 2013) was associated with non-synonymous mutations and a higher mortality rate. Phylogeographic analyses pointed to Riyadh of Saudi Arabia and Abu Dhabi of the United Arab Emirates as the hubs for both local and international spread of MERS-CoV. CONCLUSIONS: MERS-CoV remains primarily locally transmitted in the Middle East, with opportunistic exportation to other continents and a potential of causing transmission clusters of human cases. Animal contact is associated with a higher risk of death, but the association differs by age and sex. Transportation network is the leading driver for the spatial diffusion of the disease. These findings how this pathogen spread are helpful for targeting public health surveillance and interventions to control endemics and to prevent a potential pandemic.

Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: a retrospective observational study.

BACKGROUND: Wuhan was the first epicentre of COVID-19 in the world, accounting for 80% of cases in China during the first wave. We aimed to assess household transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and risk factors associated with infectivity and susceptibility to infection in Wuhan. METHODS: This retrospective cohort study included the households of all laboratory-confirmed or clinically confirmed COVID-19 cases and laboratory-confirmed asymptomatic SARS-CoV-2 infections identified by the Wuhan Center for Disease Control and Prevention between Dec 2, 2019, and April 18, 2020. We defined households as groups of family members and close relatives who did not necessarily live at the same address and considered households that shared common contacts as epidemiologically linked. We used a statistical transmission model to estimate household secondary attack rates and to quantify risk factors associated with infectivity and susceptibility to infection, accounting for individual-level exposure history. We assessed how intervention policies affected the household reproductive number, defined as the mean number of household contacts a case can infect. FINDINGS: 27 101 households with 29 578 primary cases and 57 581 household contacts were identified. The secondary attack rate estimated with the transmission model was 15·6% (95% CI 15·2-16·0), assuming a mean incubation period of 5 days and a maximum infectious period of 22 days. Individuals aged 60 years or older were at a higher risk of infection with SARS-CoV-2 than all other age groups. Infants aged 0-1 years were significantly more likely to be infected than children aged 2-5 years (odds ratio [OR] 2·20, 95% CI 1·40-3·44) and children aged 6-12 years (1·53, 1·01-2·34). Given the same exposure time, children and adolescents younger than 20 years of age were more likely to infect others than were adults aged 60 years or older (1·58, 1·28-1·95). Asymptomatic individuals were much less likely to infect others than were symptomatic cases (0·21, 0·14-0·31). Symptomatic cases were more likely to infect others before symptom onset than after (1·42, 1·30-1·55). After mass isolation of cases, quarantine of household contacts, and restriction of movement policies were implemented, household reproductive numbers declined by 52% among primary cases (from 0·25 [95% CI 0·24-0·26] to 0·12 [0·10-0·13]) and by 63% among secondary cases (from 0·17 [0·16-0·18] to 0·063 [0·057-0·070]). INTERPRETATION: Within households, children and adolescents were less susceptible to SARS-CoV-2 infection but were more infectious than older individuals. Presymptomatic cases were more infectious and individuals with asymptomatic infection less infectious than symptomatic cases. These findings have implications for devising interventions for blocking household transmission of SARS-CoV-2, such as timely vaccination of eligible children once resources become available. FUNDING: National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, US National Institutes of Health, and US National Science Foundation.

Epidemiological parameters of COVID-19 and its implication for infectivity among patients in China, 1 January to 11 February 2020.

BackgroundThe natural history of disease in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remained obscure during the early pandemic.AimOur objective was to estimate epidemiological parameters of coronavirus disease (COVID-19) and assess the relative infectivity of the incubation period.MethodsWe estimated the distributions of four epidemiological parameters of SARS-CoV-2 transmission using a large database of COVID-19 cases and potential transmission pairs of cases, and assessed their heterogeneity by demographics, epidemic phase and geographical region. We further calculated the time of peak infectivity and quantified the proportion of secondary infections during the incubation period.ResultsThe median incubation period was 7.2 (95% confidence interval (CI): 6.9‒7.5) days. The median serial and generation intervals were similar, 4.7 (95% CI: 4.2‒5.3) and 4.6 (95% CI: 4.2‒5.1) days, respectively. Paediatric cases < 18 years had a longer incubation period than adult age groups (p = 0.007). The median incubation period increased from 4.4 days before 25 January to 11.5 days after 31 January (p < 0.001), whereas the median serial (generation) interval contracted from 5.9 (4.8) days before 25 January to 3.4 (3.7) days after. The median time from symptom onset to discharge was also shortened from 18.3 before 22 January to 14.1 days after. Peak infectivity occurred 1 day before symptom onset on average, and the incubation period accounted for 70% of transmission.ConclusionThe high infectivity during the incubation period led to short generation and serial intervals, necessitating aggressive control measures such as early case finding and quarantine of close contacts.

Meteorological conditions and nonpharmaceutical interventions jointly determined local transmissibility of COVID-19 in 41 Chinese cities: A retrospective observational study.

BACKGROUND: Before effective vaccines become widely available, sufficient understanding of the impacts of climate, human movement and non-pharmaceutical interventions on the transmissibility of COVID-19 is needed but still lacking. METHODS: We collected by crowdsourcing a database of 11 003 COVID-19 cases from 305 cities outside Hubei Province from December 31, 2019 to April 27, 2020. We estimated the daily effective reproduction numbers (Rt ) of COVID-19 in 41 cities where the crowdsourced case data are comparable to the official surveillance data. The impacts of meteorological variables, human movement indices and nonpharmaceutical emergency responses on Rt were evaluated with generalized estimation equation models. FINDINGS: The median Rt was 0•46 (IQR: 0•37-0•87) in the northern cities, higher than 0•20 (IQR: 0•09-0•52) in the southern cities (p=0•004). A higher local transmissibility of COVID-19 was associated with a low temperature, a relative humidity near 70-75%, and higher intracity and intercity human movement. An increase in temperature from 0℃ to 20℃ would reduce Rt by 30% (95 CI 10-46%). A further increase to 30℃ would result in another 17% (95% CI 5-27%) reduction. An increase in relative humidity from 40% to 75% would raise the transmissibility by 47% (95% CI 9-97%), but a further increase to 90% would reduce the transmissibility by 12% (95% CI 4-19%). The decrease in intracity human movement as a part of the highest-level emergency response in China reduced the transmissibility by 36% (95% CI 27-44%), compared to 5% (95% CI 1-9%) for restricting intercity transport. Other nonpharmaceutical interventions further reduced Rt by 39% (95% CI 31-47%). INTERPRETATION: Climate can affect the transmission of COVID-19 where effective interventions are implemented. Restrictions on intracity human movement may be needed in places where other nonpharmaceutical interventions are unable to mitigate local transmission. FUNDING: China Mega-Project on Infectious Disease Prevention; U.S. National Institutes of Health and National Science Foundation.

Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study.

BACKGROUND: As of June 8, 2020, the global reported number of COVID-19 cases had reached more than 7 million with over 400 000 deaths. The household transmissibility of the causative pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains unclear. We aimed to estimate the secondary attack rate of SARS-CoV-2 among household and non-household close contacts in Guangzhou, China, using a statistical transmission model. METHODS: In this retrospective cohort study, we used a comprehensive contact tracing dataset from the Guangzhou Center for Disease Control and Prevention to estimate the secondary attack rate of COVID-19 (defined as the probability that an infected individual will transmit the disease to a susceptible individual) among household and non-household contacts, using a statistical transmission model. We considered two alternative definitions of household contacts in the analysis: individuals who were either family members or close relatives, such as parents and parents-in-law, regardless of residential address, and individuals living at the same address regardless of relationship. We assessed the demographic determinants of transmissibility and the infectivity of COVID-19 cases during their incubation period. FINDINGS: Between Jan 7, 2020, and Feb 18, 2020, we traced 195 unrelated close contact groups (215 primary cases, 134 secondary or tertiary cases, and 1964 uninfected close contacts). By identifying households from these groups, assuming a mean incubation period of 5 days, a maximum infectious period of 13 days, and no case isolation, the estimated secondary attack rate among household contacts was 12·4% (95% CI 9·8-15·4) when household contacts were defined on the basis of close relatives and 17·1% (13·3-21·8) when household contacts were defined on the basis of residential address. Compared with the oldest age group (≥60 years), the risk of household infection was lower in the youngest age group (<20 years; odds ratio [OR] 0·23 [95% CI 0·11-0·46]) and among adults aged 20-59 years (OR 0·64 [95% CI 0·43-0·97]). Our results suggest greater infectivity during the incubation period than during the symptomatic period, although differences were not statistically significant (OR 0·61 [95% CI 0·27-1·38]). The estimated local reproductive number (R) based on observed contact frequencies of primary cases was 0·5 (95% CI 0·41-0·62) in Guangzhou. The projected local R, had there been no isolation of cases or quarantine of their contacts, was 0·6 (95% CI 0·49-0·74) when household was defined on the basis of close relatives. INTERPRETATION: SARS-CoV-2 is more transmissible in households than SARS-CoV and Middle East respiratory syndrome coronavirus. Older individuals (aged ≥60 years) are the most susceptible to household transmission of SARS-CoV-2. In addition to case finding and isolation, timely tracing and quarantine of close contacts should be implemented to prevent onward transmission during the viral incubation period. FUNDING: US National Institutes of Health, Science and Technology Plan Project of Guangzhou, Project for Key Medicine Discipline Construction of Guangzhou Municipality, Key Research and Development Program of China.