scholarly journals Inference of seasonal and pandemic influenza transmission dynamics

2015 ◽  
Vol 112 (9) ◽  
pp. 2723-2728 ◽  
Author(s):  
Wan Yang ◽  
Marc Lipsitch ◽  
Jeffrey Shaman

The inference of key infectious disease epidemiological parameters is critical for characterizing disease spread and devising prevention and containment measures. The recent emergence of surveillance records mined from big data such as health-related online queries and social media, as well as model inference methods, permits the development of new methodologies for more comprehensive estimation of these parameters. We use such data in conjunction with Bayesian inference methods to study the transmission dynamics of influenza. We simultaneously estimate key epidemiological parameters, including population susceptibility, the basic reproductive number, attack rate, and infectious period, for 115 cities during the 2003–2004 through 2012–2013 seasons, including the 2009 pandemic. These estimates discriminate key differences in the epidemiological characteristics of these outbreaks across 10 y, as well as spatial variations of influenza transmission dynamics among subpopulations in the United States. In addition, the inference methods appear to compensate for observational biases and underreporting inherent in the surveillance data.

2020 ◽  
Vol 148 ◽  
Author(s):  
Arnab Chanda

Abstract The spread of COVID-19 is recent in India, which has within 4 months caused over 190 000 infections, as of 1 June 2020, despite four stringent lockdowns. With the current rate of the disease transmission in India, which is home to over 1.35 billion people, the infection spread is predicted to be worse than the USA in the upcoming months. To date, there is a major lack of understanding of the transmission dynamics and epidemiological characteristics of the disease in India, inhibiting effective measures to control the pandemic. We collected all the available data of the individual patients, cases and a range of parameters such as population distribution, testing and healthcare facilities, and weather, across all Indian states till May 2020. Numerical analysis was conducted to determine the effect of each parameter on the COVID-19 situation in India. A significant amount of local transmission in India initiated with travellers returning from abroad. Maharashtra, Tamil Nadu and Delhi are currently the top three infected states in India with doubling time of 14.5 days. The average recovery rate across Indian states is 42%, with a mortality rate below 3%. The rest 55% are currently active cases. In total, 88% of the patients experienced symptoms of high fever, 68% suffered from dry cough and 7.1% patients were asymptomatic. In total, 66.8% patients were males, 73% were in the age group of 20–59 years and over 83% recovered in 11–25 days. Approximately 3.4 million people were tested between 1 April and 25 May 2020, out of which 4% were detected COVID-19-positive. Given the current doubling time of infections, several states may face a major shortage of public beds and healthcare facilities soon. Weather has minimal effect on the infection spread in most Indian states. The study results will help policymakers to predict the trends of the disease spread in the upcoming months and devise better control measures.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter J. Bonney ◽  
Sasidhar Malladi ◽  
Amos Ssematimba ◽  
Erica Spackman ◽  
Mia Kim Torchetti ◽  
...  

AbstractLimiting spread of low pathogenicity avian influenza (LPAI) during an outbreak is critical to reduce the negative impact on poultry producers and local economies. Mathematical models of disease transmission can support outbreak control efforts by estimating relevant epidemiological parameters. In this article, diagnostic testing data from each house on a premises infected during a LPAI H5N2 outbreak in the state of Minnesota in the United States in 2018 was used to estimate the time of virus introduction and adequate contact rate, which determines the rate of disease spread. A well-defined most likely time of virus introduction, and upper and lower 95% credibility intervals were estimated for each house. The length of the 95% credibility intervals ranged from 11 to 22 with a mean of 17 days. In some houses the contact rate estimates were also well-defined; however, the estimated upper 95% credibility interval bound for the contact rate was occasionally dependent on the upper bound of the prior distribution. The estimated modes ranged from 0.5 to 6.0 with a mean of 2.8 contacts per day. These estimates can be improved with early detection, increased testing of monitored premises, and combining the results of multiple barns that possess similar production systems.


2022 ◽  
Author(s):  
Fabrizio Menardo

Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether difference in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, and molecular clock), and found that all these factors, except the length of the infectious period and R0, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: 1) clustering results and TBL depend on many factors that have nothing to do with transmission, 2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamid Khataee ◽  
Istvan Scheuring ◽  
Andras Czirok ◽  
Zoltan Neufeld

AbstractA better understanding of how the COVID-19 pandemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number ($$R_0$$ R 0 ) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the pandemic.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bingyi Yang ◽  
Angkana T. Huang ◽  
Bernardo Garcia-Carreras ◽  
William E. Hart ◽  
Andrea Staid ◽  
...  

AbstractNon-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (Reff) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median Reff below 1 when combined with either stay at home orders (median Reff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median Reff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.


2022 ◽  
pp. 073112142110677
Author(s):  
Rebecca Farber ◽  
Joseph Harris

COVID-19 has focused global attention on disease spread across borders. But how has research on infectious and noncommunicable disease figured into the sociological imagination historically, and to what degree has American medical sociology examined health problems beyond U.S. borders? Our 35-year content analysis of 2,588 presentations in the American Sociological Association’s (ASA) Section on Medical Sociology and 922 articles within the section’s official journal finds less than 15 percent of total research examined contexts outside the United States. Research on three infectious diseases in the top eight causes of death in low-income countries (diarrheal disease, malaria, and tuberculosis [TB]) and emerging diseases—Ebola, Middle East Respiratory Syndrome (MERS), and Severe Acute Respiratory Syndrome (SARS)—was nearly absent, as was research on major noncommunicable diseases. Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS) received much more focus, although world regions hit hardest received scant attention. Interviews suggest a number of factors shape geographic foci of research, but this epistemic parochialism may ultimately impoverish sociological understanding of illness and disease.


2017 ◽  
Vol 76 (5) ◽  
pp. 445-452 ◽  
Author(s):  
Eduardo E. Valverde ◽  
Alexandra M. Oster ◽  
Songli Xu ◽  
Joel O. Wertheim ◽  
Angela L. Hernandez

Plant Disease ◽  
2009 ◽  
Vol 93 (6) ◽  
pp. 673-673 ◽  
Author(s):  
C. J. Li ◽  
Z. F. Wang ◽  
N. Chen ◽  
Z. B. Nan

Orchardgrass or cocksfoot (Dactylis glomerata L.) has been widely cultivated as a forage crop in many provinces of China (1). It is also a native perennial forage grass, which grows at the edge of forests, shrubs, and mountainous grasslands in Xinjiang and Sichuan (2). In September of 2007, signs of choke disease on orchardgrass were observed in a native grassland under birch woodland near Altai City, Xinjiang, China. Stromata, which formed on culms of diseased grass, enclosing the inflorescence and leaf sheath, were 4.5 to 5.5 mm long, smooth or wrinkled, white and later becoming yellowish or yellow, tuberculate, dry, and covered with perithecia. Inflorescences surrounded by fungal stromata were choked and failed to mature, thus restricting seed production. Pure cultures were obtained by directly scraping stromata from the surface and incubating it on antibiotic potato dextrose agar (PDA). The colonies were cottony, white on the upper surface, and white to yellow on the reverse. The growth rate was 13 to 21 mm per week at 25°C on PDA. Conidia were hyaline, lunate to reniform, and measured 4.1 ± 0.5 × 2.2 ± 0.5 μm. They accumulated in small globose heads at the tips of conidiogenous cells and were produced singly on conidiophores of 13 to 33 μm long and 2.7 to 4.1 μm wide at the base. Internal transcribed spacer (ITS) sequence by BLAST search had 99% similarity with an Epichloë typhina isolate of orchardgrass in Spain (GenBank Accession No. AM262420.1). Cultural characteristics, microscopic examination, and phylogenetic analysis showed that this choke disease on D. glomerata was caused by the fungus E. typhina (Pers.) Tul. & C. Tul. as described by White (4). To our knowledge, this is the first report of E. typhina causing choke disease on orchardgrass in China. The pathogen has been identified in France, England, Germany, Sweden, Switzerland, and the United States (3,4) with the same symptoms as those reported here. In 1997, choke disease was found in 70% of the fields in the Willamette Valley of Oregon, with disease incidences ranging from 0.05 to 28%. It was predicted to increase and spread under the prevailing climatic conditions (3). This new disease report is to provide observational and diagnostic information to help with recognition and prevention of disease spread in orchardgrass cultivation regions of China. References: (1) X. R. Chao et al. Shandong Agric. Sci. 1:7, 2005. (2) S. X. Jia, ed. China Forage Plant Flora. China Agriculture Press, Beijing, 1987. (3) W. F. Pfender and S. C. Alderman. Plant Dis. 83:754, 1999. (4) J. W. White. Mycologia 85:444, 1993.


Plant Disease ◽  
2011 ◽  
Vol 95 (7) ◽  
pp. 873-873 ◽  
Author(s):  
L. M. Kawchuk ◽  
R. J. Howard ◽  
R. D. Peters ◽  
K. I. Al-Mughrabi

Late blight is caused by the oomycete Phytophthora infestans (Mont.) de Bary and is one of the most devastating diseases of potato and tomato. Late blight occurs in all major potato- and tomato-growing regions of Canada. Its incidence in North America increased during 2009 and 2010 (2). Foliar disease symptoms appeared earlier than usual (June rather than July) and coincided with the identification of several new P. infestans genotypes in the United States, each with unique characteristics. Prior to 2007, isolates collected from potato and tomato crops were mainly US8 or US11 genotypes (1). However, P. infestans populations in the United States have recently experienced a major genetic evolution, producing isolates with unique genotypes and epidemiological characteristics in Florida and throughout the northeastern states (2). Recent discoveries of tomato transplants with late blight for sale at Canadian retail outlets prompted an examination of the genotypes inadvertently being distributed and causing disease in commercial production areas in Canada. Analysis of isolates of P. infestans from across Canada in 2010 identified the US23 genotype for the first time from each of the four western provinces (Manitoba, Saskatchewan, Alberta, and British Columbia) but not from eastern Canada. Allozyme banding patterns at the glucose phosphate isomerase (Gpi) locus indicated a 100/100 profile consistent with US6 and US23 genotypes (4). Mating type assays confirmed the isolates to be A1 and in vivo metalaxyl sensitivity was observed. Restriction fragment length polymorphic analysis of 50 isolates from western Canada with the multilocus RG57 sequence and EcoRI produced the DNA pattern 1, 2, 5, 6, 10, 13, 14, 17, 20, 21, 24, 24a, 25 that was indicative of US23 (3). The recently described P. infestans genotype US23 appears to be more aggressive on tomato, and although isolates were recovered from both tomato and potato, disease symptoms were often more severe on tomato. Results indicate that movement and evolution of new P. infestans genotypes have contributed to the increased incidence of late blight and that movement of the pathogen on retail plantlets nationally and internationally may provide an additional early season source of inoculum. A major concern is that the introduced new A1 populations in western Canada have established a dichotomy with the endogenous A2 populations in eastern Canada, increasing the potential for sexual recombination producing oospores and additional genotypes should these populations merge. References: (1) Q. Chen et al. Am. J. Potato Res. 80:9, 2003. (2) K. Deahl. (Abstr.) Phytopathology 100(suppl.):S161, 2010. (3) S. B. Goodwin et al. Curr. Genet. 22:107, 1992. (4) S. B. Goodwin et al. Phytopathology 88:939, 2004.


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