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 contac...

Pandemic influenza A (H1N1) 2009 (pandemic H1N1) is spreading throughout the planet. It has become the dominant strain in the southern hemisphere, where the influenza season is underway. Here, based on reported case clusters in the USA, we estimate the household secondary attack rate for pandemic H1N1 to be 27.3% (95% CI: 12.2%-50.5%). From a school outbreak, we estimate a school child infects 2.4 (95% CI: 1.8-3.2) other children within the school. We estimate the basic reproductive number, R 0 , to range from 1.3-1.7 and the generation interval to range from 2.6-3.2 days. We use a simulation model to evaluate the effectiveness of vaccination strategies in the USA for the Fall, 2009. If vaccine were available soon enough, vaccination of children, followed by adults, reaching 70% overall coverage, in addition to high risk and essential workforce groups, could mitigate a severe epidemic.Pandemic H1N1, which first emerged in Mexico in , spread worldwide, resulting in more than 130,000 laboratory-confirmed cases and 800 deaths in over 100 countries by midJuly (1). The global distribution of this novel strain prompted the World Health Organization to declare the first influenza pandemic of the 21st century in June 2009 (2). Initially, most cases were clustered in households (3-6) and schools (7) with over 50% of the reported cases in school children in the 5-18 year old age range. A recent analysis of data from the United States, Canada, the United Kingdom, and the European Union suggests case fatality ratios ranging from 0.20%-0.68% in these regions and a higher case fatality ratio in Mexico of 1.23% (95% CI 1.03%-1.47%) (8).Both pandemic and seasonal influenza cause sustained epidemics in the upper northern hemisphere (above latitude ~ 20°N) and lower southern hemisphere (below latitude ~ 20°S) during the respective late Fall to early Spring months, with epidemics in the more tropical regions (between latitudes ~ 20°S and 20°N) occurring sporadically, but sometimes corresponding to the rainy season. The last influenza pandemic was the Hong Kong A (H3N2) * To whom correspondence should be addressed. longini@scharp.org . 1957 -1958 , caused mid-Summer, 1957, outbreaks in Louisiana schools that were open in the Summer because of the need for children helping with the Spring harvest (11). However, there was no extensive community-wide spread of influenza A (H2N2) in the USA until the Fall of 1957, with the national level epidemic rising in September and peaking in October. Pandemic H1N1 will probably spread in a similar spatio-temporal pattern as previous pandemics, but accelerated due to increased air travel (12). Supporting Online MaterialEstimates of the transmissibility of pandemic H1N1are crucial to devising effective mitigation strategies. Historically, the best characterization of influenza transmissibility has been based on the household secondary attack rate. The household secondary attack rate is the probability (sometimes expressed as a percent) that an infected person in the household will infect a...

More than half of identified cases result from person-to-person transmission.

TOC summary line: Nipah virus was likely transmitted from fruit bats to humans by drinking fresh date palm sap.

In an important paper, M.E.J. Newman claimed that a general network-based stochastic SusceptibleInfectious-Removed (SIR) epidemic model is isomorphic to a bond percolation model, where the bonds are the edges of the contact network and the bond occupation probability is equal to the marginal probability of transmission from an infected node to a susceptible neighbor. In this paper, we show that this isomorphism is incorrect and define a semi-directed random network we call the epidemic percolation network that is exactly isomorphic to the SIR epidemic model in any finite population. In the limit of a large population, (i) the distribution of (self-limited) outbreak sizes is identical to the size distribution of (small) out-components, (ii) the epidemic threshold corresponds to the phase transition where a giant strongly-connected component appears, (iii) the probability of a large epidemic is equal to the probability that an initial infection occurs in the giant in-component, and (iv) the relative final size of an epidemic is equal to the proportion of the network contained in the giant out-component. For the SIR model considered by Newman, we show that the epidemic percolation network predicts the same mean outbreak size below the epidemic threshold, the same epidemic threshold, and the same final size of an epidemic as the bond percolation model. However, the bond percolation model fails to predict the correct outbreak size distribution and probability of an epidemic when there is a nondegenerate infectious period distribution. We confirm our findings by comparing predictions from percolation networks and bond percolation models to the results of simulations. In an appendix, we show that an isomorphism to an epidemic percolation network can be defined for any time-homogeneous stochastic SIR model.