Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (COVID-19).

Background: Estimation of the fraction and contagiousness of undocumented novel coronavirus (COVID-19) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Many mild infections are typically not reported and, depending on their contagiousness, may support stealth transmission and the spread of documented infection. Methods: Here we use observations of reported infection and spread within China in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with the emerging coronavirus, including the fraction of undocumented infections and their contagiousness. Results: We estimate 86% of all infections were undocumented (95% CI: [82%-90%]) prior to the Wuhan travel shutdown (January 23, 2020). Per person, these undocumented infections were 52% as contagious as documented infections ([44%-69%]) and were the source of infection for two-thirds of documented cases. Our estimate of the reproductive number (2.23; [1.77-3.00]) aligns with earlier findings; however, after travel restrictions and control measures were imposed this number falls considerably. Conclusions: A majority of COVID-19 infections were undocumented prior to implementation of control measures on January 23, and these undocumented infections substantially contributed to virus transmission. These findings explain the rapid geographic spread of COVID-19 and indicate containment of this virus will be particularly challenging. Our findings also indicate that heightened awareness of the outbreak, increased use of personal protective measures, and travel restriction have been associated with reductions of the overall force of infection; however, it is unclear whether this reduction will be sufficient to stem the virus spread

Shortcomings of Vitamin D-Based Model Simulations of Seasonal Influenza

Seasonal variation in serum concentration of the vitamin D metabolite 25(OH) vitamin D [25(OH)D], which contributes to host immune function, has been hypothesized to be the underlying source of observed influenza seasonality in temperate regions. The objective of this study was to determine whether observed 25(OH)D levels could be used to simulate observed influenza infection rates. Data of mean and variance in 25(OH)D serum levels by month were obtained from the Health Professionals Follow-up Study and used to parameterize an individual-based model of influenza transmission dynamics in two regions of the United States. Simulations were compared with observed daily influenza excess mortality data. Best-fitting simulations could reproduce the observed seasonal cycle of influenza; however, these best-fit simulations were shown to be highly sensitive to stochastic processes within the model and were unable consistently to reproduce observed seasonal patterns. In this respect the simulations with the vitamin D forced model were inferior to similar modeling efforts using absolute humidity and the school calendar as seasonal forcing variables. These model results indicate it is unlikely that seasonal variations in vitamin D levels principally determine the seasonality of influenza in temperate regions

Economic factors influencing zoonotic disease dynamics: demand for poultry meat and seasonal transmission of avian influenza in Vietnam

While climate is often presented as a key factor influencing the seasonality of diseases, the importance of anthropogenic factors is less commonly evaluated. Using a combination of methods-wavelet analysis, economic analysis, statistical and disease transmission modelling-we aimed to explore the influence of climatic and economic factors on the seasonality of H5N1 Highly Pathogenic Avian Influenza in the domestic poultry population of Vietnam. We found that while climatic variables are associated with seasonal variation in the incidence of avian influenza outbreaks in the North of the country, this is not the case in the Centre and the South. In contrast, temporal patterns of H5N1 incidence are similar across these 3 regions: periods of high H5N1 incidence coincide with Lunar New Year festival, occurring in January-February, in the 3 climatic regions for 5 out of the 8 study years. Yet, daily poultry meat consumption drastically increases during Lunar New Year festival throughout the country. To meet this rise in demand, poultry production and trade are expected to peak around the festival period, promoting viral spread, which we demonstrated using a stochastic disease transmission model. This study illustrates the way in which economic factors may influence the dynamics of livestock pathogens

Environmental Predictors of Seasonal Influenza Epidemics across Temperate and Tropical Climates

Human influenza infections exhibit a strong seasonal cycle in temperate regions. Recent laboratory and epidemiological evidence suggests that low specific humidity conditions facilitate the airborne survival and transmission of the influenza virus in temperate regions, resulting in annual winter epidemics. However, this relationship is unlikely to account for the epidemiology of influenza in tropical and subtropical regions where epidemics often occur during the rainy season or transmit year-round without a well-defined season. We assessed the role of specific humidity and other local climatic variables on influenza virus seasonality by modeling epidemiological and climatic information from 78 study sites sampled globally. We substantiated that there are two types of environmental conditions associated with seasonal influenza epidemics: “cold-dry” and “humid-rainy”. For sites where monthly average specific humidity or temperature decreases below thresholds of approximately 11–12 g/kg and 18–21°C during the year, influenza activity peaks during the cold-dry season (i.e., winter) when specific humidity and temperature are at minimal levels. For sites where specific humidity and temperature do not decrease below these thresholds, seasonal influenza activity is more likely to peak in months when average precipitation totals are maximal and greater than 150 mm per month. These findings provide a simple climate-based model rooted in empirical data that accounts for the diversity of seasonal influenza patterns observed across temperate, subtropical and tropical climates

Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)

Estimation of the prevalence and contagiousness of undocumented novel coronavirus (SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV2, including the fraction of undocumented infections and their contagiousness. We estimate 86% of all infections were undocumented (95% CI: [82%–90%]) prior to 23 January 2020 travel restrictions. Per person, the transmission rate of undocumented infections was 55% of documented infections ([46%–62%]), yet, due to their greater numbers, undocumented infections were the infection source for 79% of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Transmission Characteristics of the 2009 H1N1 Influenza Pandemic: Comparison of 8 Southern Hemisphere Countries

While in Northern hemisphere countries, the pandemic H1N1 virus (H1N1pdm) was introduced outside of the typical influenza season, Southern hemisphere countries experienced a single wave of transmission during their 2009 winter season. This provides a unique opportunity to compare the spread of a single virus in different countries and study the factors influencing its transmission. Here, we estimate and compare transmission characteristics of H1N1pdm for eight Southern hemisphere countries/states: Argentina, Australia, Bolivia, Brazil, Chile, New Zealand, South Africa and Victoria (Australia). Weekly incidence of cases and age-distribution of cumulative cases were extracted from public reports of countries' surveillance systems. Estimates of the reproduction numbers, R0, empirically derived from the country-epidemics' early exponential phase, were positively associated with the proportion of children in the populations (p = 0.004). To explore the role of demography in explaining differences in transmission intensity, we then fitted a dynamic age-structured model of influenza transmission to available incidence data for each country independently, and for all the countries simultaneously. Posterior median estimates of R0 ranged 1.2–1.8 for the country-specific fits, and 1.29–1.47 for the global fits. Corresponding estimates for overall attack-rate were in the range 20–50%. All model fits indicated a significant decrease in susceptibility to infection with age. These results confirm the transmissibility of the 2009 H1N1 pandemic virus was relatively low compared with past pandemics. The pattern of age-dependent susceptibility found confirms that older populations had substantial – though partial - pre-existing immunity, presumably due to exposure to heterologous influenza strains. Our analysis indicates that between-country-differences in transmission were at least partly due to differences in population demography

Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States

Here, the authors demonstrate that variations of absolute humidity explain both the onset of wintertime influenza transmission and the overarching seasonality of this pathogen in temperate regions

The community impact of the 2009 influenza pandemic in the WHO European Region: a comparison with historical seasonal data from 28 countries

Contains fulltext : 109779.pdf (publisher's version ) (Open Access)BACKGROUND: The world has recently experienced the first influenza pandemic of the 21st century that lasted 14 months from June 2009 to August 2010. This study aimed to compare the timing, geographic spread and community impact during the winter wave of influenza pandemic A (H1N1) 2009 to historical influenza seasons in countries of the WHO European region. METHODS: We assessed the timing of pandemic by comparing the median peak of influenza activity in countries of the region during the last seven influenza seasons. The peaks of influenza activity were selected by two independent researchers using predefined rules. The geographic spread was assessed by correlating the peak week of influenza activity in included countries against the longitude and latitude of the central point in each country. To assess the community impact of pandemic influenza, we constructed linear regression models to compare the total and age-specific influenza-like-illness (ILI) or acute respiratory infection (ARI) rates reported by the countries in the pandemic season to those observed in the previous six influenza seasons. RESULTS: We found that the influenza activity reached its peak during the pandemic, on average, 10.5 weeks (95% CI 6.4-14.2) earlier than during the previous 6 seasons in the Region, and there was a west to east spread of pandemic A(H1N1) influenza virus in the western part of the Region. A regression analysis showed that the total ILI or ARI rates were not higher than historical rates in 19 of the 28 countries. However, in countries with age-specific data, there were significantly higher consultation rates in the 0-4 and/or 5-14 age groups in 11 of the 20 countries. CONCLUSIONS: Using routine influenza surveillance data, we found that pandemic influenza had several differential features compared to historical seasons in the region. It arrived earlier, caused significantly higher number of outpatient consultations in children in most countries and followed west to east spread that was previously observed during some influenza seasons with dominant A (H3N2) ifluenza viruses. The results of this study help to understand the epidemiology of 2009 influenza pandemic and can be used for pandemic preparedness planning