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"transmission dynamics"
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Transmission Dynamics of African Swine Fever Virus, South Korea, 2019
African swine fever (ASF) is a substantial concern for global food production and security. However, lack of epidemiologic data in affected areas has limited the knowledge of the main drivers of ASF virus (ASFV) transmission. To assess the role of vehicle movements and wild boar populations in spreading ASFV to pig farms in South Korea, we combined data generated by ASF surveillance on pig farms and of wild boars with nationwide global positioning system–based tracking data for vehicles involved in farming activities. Vehicle movements from infected premises were associated with a higher probability of ASFV incursion into a farm than was geographic proximity to ASFV-infected wild boar populations. Although ASFV can spill over from infected wild boars into domestic pigs, vehicles played a substantial role in spreading infection between farms, despite rapid on-farm detection and culling. This finding highlights the need for interventions targeting farm-to-farm and wildlife-to-farm interfaces.
Journal Article
Incidence and Transmission Dynamics of Bordetella pertussis Infection in Rural and Urban Communities, South Africa, 2016‒2018
We conducted 3 prospective cohort studies (2016-2018), enrolling persons from 2 communities in South Africa. Nasopharyngeal swab specimens were collected twice a week from participants. Factors associated with Bordetella pertussis incidence, episode duration, and household transmission were determined by using Poisson regression, Weibull accelerated time-failure, and logistic regression hierarchical models, respectively. Among 1,684 participants, 118 episodes of infection were detected in 107 participants (incidence 0.21, 95% CI 0.17-0.25 infections/100 person-weeks). Children <5 years of age who had incomplete vaccination were more likely to have pertussis infection. Episode duration was longer for participants who had higher bacterial loads. Transmission was more likely to occur from male index case-patients and persons who had >7 days infection duration. In both communities, there was high incidence of B. pertussis infection and most cases were colonized.
Journal Article
A Prospective Study on the Transmission dynamics of Corona virus disease (2019) (COVID-19) among Household contacts in Delhi, India. version 1; peer review: awaiting peer review
Background: This study was conducted to understand the transmission dynamics of COVID-19 virus among the household contacts of RT-PCR confirmed cases to have an insight on key epidemiological characteristics of the infection.
Methods: This was a prospective case-ascertained study conducted among the contacts of laboratory-confirmed COVID-19 cases residing in the same household in the Central and North-East districts of Delhi between 28
th December 2020, and 28
th June 2021. Data and specimen for reverse transcription polymerase chain reaction (RT-PCR) and serology were collected from the primary case and their contacts on day one of the visit, and follow-up collection of data and specimen was done on day 7, 14 and 28. A daily symptom diary was also maintained for all the primary cases and their contacts till 28 days from enrolment in the study. A total of 109 houses were enrolled in the study.
Results: The secondary attack rate (SAR) estimated among the household contacts was 13.86% [95% C.I. 9.71%, 19.39%] and the secondary infection rate was 33.16% [95% C.I. 26.97%, 40.00%]. The serial interval and basic reproduction number (R0) within the household were estimated to be 3.6± 5.73 days and 1.26 [95% C.I. 1.21-1.31], respectively. Significant predictors of the infection were location of household in central district (SAR = 20% [13.75, 28.16]) versus North-East District (SAR = 4.87% [1.83-12.35]) p= 0.002, sharing of utensils (SAR= 42.85% [14.26-77.11], p=0.02), and using the room to sleep where a specific case has been isolated (SAR= 25% [12.97-42.71], p=0.047). Transmission from the symptomatic primary case was observed to be five times higher.
Conclusion: Our analysis showed that the secondary infection rate was higher among household contacts. This study suggests a dose-response association between severity of the primary case of SARS CoV-2 and infection among contacts.
Journal Article
Infectious disease transmission and contact networks in wildlife and livestock
The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.
Journal Article
Transmission dynamics of COVID-19 in Wuhan, China: effects of lockdown and medical resources
Due to the strong infectivity of COVID-19, it spread all over the world in about three months and thus has been studied from different aspects including its source of infection, pathological characteristics, diagnostic technology and treatment. Yet, the influences of control strategies on the transmission dynamics of COVID-19 are far from being well understood. In order to reveal the mechanisms of disease spread, we present dynamical models to show the propagation of COVID-19 in Wuhan. Based on mathematical analysis and data analysis, we systematically explore the effects of lockdown and medical resources on the COVID-19 transmission in Wuhan. It is found that the later lockdown is adopted by Wuhan, the fewer people will be infected in Wuhan, and nevertheless it will have an impact on other cities in China and even the world. Moreover, the richer the medical resources, the higher the peak of new infection, but the smaller the final scale. These findings well indicate that the control measures taken by the Chinese government are correct and timely.
Journal Article
Dynamiques de transmission en milieu humanitaire : quels rôles et impacts sur les collectifs d’intervention ?
Since the 1990s, humanitarian aid has been undergoing a process of professionalization through rationalization, with increasingly standardized procedures designed to ensure transparency and justify actions taken. However, this organizational evolution generates tensions between standardized prescriptions and the complex realities of the field, affecting both the performance and the health of humanitarian workers, particularly as revealed through the ways in which knowledge and practices are transmitted within intervention collectives. This qualitative study aims to characterize these transmission dynamics in the field and to understand their roles and impacts in this context of professionalization. Conducted in West Africa, it relies on semi-structured interviews, observations, and a participatory photographic project. The results reveal a segmentation of transmission dynamics according to profession, status, and workspace. They highlight above all the complementarity between formal and informal transmissions, which proves indispensable for intervention collectives to cope with the tensions between organizational prescriptions and field realities. This complementarity sustains a process of renormalization (collective adjustments of norms) through which teams maintain both operational performance and workers’ health.
Journal Article
Early Transmission Dynamics, Spread, and Genomic Characterization of SARS-CoV-2 in Panama
We report an epidemiologic analysis of 4,210 cases of infection with severe acute respiratory syndrome coronavirus 2 and genetic analysis of 313 new near-complete virus genomes in Panama during March 9-April 16, 2020. Although containment measures reduced R
and R
, they did not interrupt virus spread in the country.
Journal Article
Inference of seasonal and pandemic influenza transmission dynamics
Significance Infectious disease surveillance systems are powerful tools for monitoring and understanding infectious disease dynamics; however, underreporting (due to both unreported and asymptomatic infections) and observation errors in these systems create challenges for delineating a complete picture of infectious disease epidemiology. This issue is true for influenza, an infectious disease of pandemic potential. Here we develop and present influenza inference systems capable of compensating for observational biases and underreporting. Using both Google Flu Trends and Centers for Disease Control and Prevention data in conjunction with Bayesian model inference methods, we are able to infer the evolving epidemiological features of influenza and its impacts among the large population during 2003−2013, including the 2009 pandemic. In addition, differences among regions within the United States are identified.
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.
Journal Article
Phylogenetic Analysis of Transmission Dynamics of Dengue in Large and Small Population Centers, Northern Ecuador
Although dengue is typically considered an urban disease, rural communities are also at high risk. To clarify dynamics of dengue virus (DENV) transmission in settings with characteristics generally considered rural (e.g., lower population density, remoteness), we conducted a phylogenetic analysis in 6 communities in northwestern Ecuador. DENV RNA was detected by PCR in 121/488 serum samples collected from febrile case-patients during 2019-2021. Phylogenetic analysis of 27 samples from Ecuador and other countries in South America confirmed that DENV-1 circulated during May 2019-March 2020 and DENV-2 circulated during December 2020-July 2021. Combining locality and isolation dates, we found strong evidence that DENV entered Ecuador through the northern province of Esmeraldas. Phylogenetic patterns suggest that, within this province, communities with larger populations and commercial centers were more often the source of DENV but that smaller, remote communities also play a role in regional transmission dynamics.
Journal Article