Combining molecular typing and spatial pattern analysis to identify areas of high tuberculosis transmission in a moderate-incidence county in Taiwan.
Ontology highlight
ABSTRACT:
SUBMITTER: Chen YY
PROVIDER: S-EPMC5511213 | biostudies-literature | 2017 Jul
REPOSITORIES: biostudies-literature
Publications
Combining molecular typing and spatial pattern analysis to identify areas of high tuberculosis transmission in a moderate-incidence county in Taiwan.
Chen Yih-Yuan YY Chang Jia-Ru JR Wu Chih-Da CD Yeh Yen-Po YP Yang Shiu-Ju SJ Hsu Chih-Hao CH Lin Ming-Ching MC Tsai Ching-Fang CF Lin Ming-Shian MS Su Ih-Jen IJ Dou Horng-Yunn HY
Scientific reports 20170714 1
In total, 303 randomly selected clinical Mycobacterium tuberculosis (MTB) isolates from 303 patients (collected January to December 2012) in central Taiwan were examined. The major lineages found were Beijing (N = 114, 37.62%), Haarlem (N = 76, 25.08%) and East African-Indian (EAI) (N = 42, 13.86%). Notably, younger persons (≤30 years old) were 6.58 times more likely to be infected with a Beijing genotype compared to older persons (>70 years) (p < 0.05). Combining molecular typing methods and ge ...[more]
Similar Datasets
Project description:The HIV epidemic in San Mateo County is sustained by multiple overlapping risk groups and is an important hub for HIV transmission in northern California. Limited access to care has led historically to delayed clinical presentation, higher rates of opportunistic infections, and an increased prevalence of antiretroviral drug resistance. The virologic and clinical consequences of treatment within these multiple ethnic and behavioral groups are poorly understood, highlighting the need for efficient surveillance strategies that are able to elucidate transmission networks and drug resistance patterns. We obtained sequence data from a group of 316 HIV-positive individuals in the San Mateo AIDS Program over a 14-year period and integrated epidemiologic, phylogenetic, and network approaches to characterize transmission clusters, risk factors and drug resistance. Drug resistance mutations were identified using the Stanford HIV Drug Resistance Database. A maximum likelihood tree was inferred in RAxML and subjected to clustering analysis in Cluster Picker. Network analysis using pairwise genetic distances was performed in HIV-TRACE. Participants were primarily male (60%), white Hispanics and non-Hispanics (32%) and African American (20.6%). The most frequent behavior risk factor was male-male sex (33.5%), followed by heterosexual (23.4%) and injection drug use (9.5%). Nearly all sequences were subtype B (96%) with subtypes A, C, and CRF01_AE also observed. Sequences from 65% of participants had at least one drug resistance mutation. Clustered transmissions included a higher number of women when compared to non-clustered individuals and were more likely to include heterosexual or people who inject drugs (PWID). Detailed analysis of the largest network (N = 47) suggested that PWID played a central role in overall transmission of HIV-1 as well as bridging men who have sex with men (MSM) transmission with heterosexual/PWID among primarily African American men. Combined phylogenetic and network analysis of HIV sequence data identified several overlapping risk factors in the epidemic, including MSM, heterosexual and PWID transmission with a disproportionate impact on African Americans and a high prevalence of drug resistance.
| S-EPMC6292275 | biostudies-literature
Project description:Zika virus (ZIKV) is a mosquito-borne flavivirus that has recently emerged as a global health threat. The rise in ZIKV infections has driven an increased incidence of neonates born with microcephaly or other neurological malformations. Therefore, screening for ZIKV infection can considerably impact pregnant women, especially during the first trimester. The majority of ZIKV infections are mild or asymptomatic, and clinical diagnosis is inaccurate. Moreover, given the high level of cross-reactivity among flaviviruses, serological approaches to distinguish ZIKV from dengue virus (DENV) infections are complicated. We used the combination of DENV and ZIKV nonstructural protein 1 (NS1) IgG enzyme-linked immunosorbent assay (ELISA) and ZIKV NS1 blockade-of-binding (BOB) ELISA to test the convalescent sera of non-flavivirus, primary DENV, secondary DENV, and ZIKV infections. Our findings indicate that primary testing using a ZIKV NS1 IgG ELISA, the test of choice for large-scale ZIKV serosurvey studies, provided relatively high sensitivity. Moreover, the confirmation of positive ELISA results using the ZIKV NS1 BOB ELISA increased average specificity to 94.59% across serum samples. The combined use of two simple ELISAs for ZIKV serosurveys and the monitoring of ZIKV infection during pregnancy can elucidate the epidemiology, pathogenesis, and complications of ZIKV in DENV-endemic areas.
| S-EPMC9610724 | biostudies-literature
Project description:The spread of a communicable disease is a complex spatio-temporal process shaped by the specific transmission mechanism, and diverse factors including the behavior, socio-economic and demographic properties of the host population. While the key factors shaping transmission of influenza and COVID-19 are beginning to be broadly understood, making precise forecasts on case count and mortality is still difficult. In this study we introduce the concept of a universal geospatial risk phenotype of individual US counties facilitating flu-like transmission mechanisms. We call this the Universal Influenza-like Transmission (UnIT) score, which is computed as an information-theoretic divergence of the local incidence time series from an high-risk process of epidemic initiation, inferred from almost a decade of flu season incidence data gleaned from the diagnostic history of nearly a third of the US population. Despite being computed from the past seasonal flu incidence records, the UnIT score emerges as the dominant factor explaining incidence trends for the COVID-19 pandemic over putative demographic and socio-economic factors. The predictive ability of the UnIT score is further demonstrated via county-specific weekly case count forecasts which consistently outperform the state of the art models throughout the time-line of the COVID-19 pandemic. This study demonstrates that knowledge of past epidemics may be used to chart the course of future ones, if transmission mechanisms are broadly similar, despite distinct disease processes and causative pathogens.
| S-EPMC8516313 | biostudies-literature
Project description:AIM: To evaluate the incidence of Crohn's disease in Stockholm County between 1955 and 1989. METHODS: A cohort of 1936 patients with Crohn's disease was retrospectively assembled. Incidence rates and changes in disease distribution were assessed. RESULTS: The mean increase in incidence was 15% (95% confidence intervals 12% to 18%) per five year period with a mean annual incidence rate at 4.6/10(5) during the last two decades. The mean incidence for the entire study period was similar for men and women. The mean age at diagnosis increased from 25 years in 1960-64 to 32 years in 1985-89, partly because of an increasing proportion of patients aged at least 60 years at diagnosis. The proportion of patients with colonic Crohn's disease at the time of diagnosis increased from 15% to 32% (17% difference; 95% confidence intervals 12% to 23%) whereas the proportion of patients with ileocaecal disease decreased from 58% to 41% (17% difference; 95% confidence intervals 10% to 24%) during the study period. Elderly patients had a higher proportion of small bowel disease and a lower proportion of ileocolonic disease compared with the younger patients. CONCLUSION: The incidence rate of Crohn's disease in Stockholm has stabilised at 4.6/10(5) and the proportion of elderly patients has increased during a 35 year period. Colonic Crohn's disease has increased in frequency with a reciprocal decrease in ileocaecal disease.
| S-EPMC1891542 | biostudies-other
Project description:BackgroundCountries planning malaria elimination must adapt from sustaining universal control to targeted intervention and surveillance. Decisions to make this transition require interpretable information, including malaria parasite survey data. As transmission declines, observed parasite prevalence becomes highly heterogeneous with most communities reporting estimates close to zero. Absolute estimates of prevalence become hard to interpret as a measure of transmission intensity and suitable statistical methods are required to handle uncertainty of area-wide predictions that are programmatically relevant.MethodsA spatio-temporal geostatistical binomial model for Plasmodium falciparum prevalence (PfPR) was developed using data from cross-sectional surveys conducted in Somalia in 2005, 2007-2011 and 2014. The fitted model was then used to generate maps of non-exceedance probabilities, i.e. the predictive probability that the region-wide population-weighted average PfPR for children between 2 and 10 years (PfPR2-10) lies below 1 and 5%. A comparison was carried out with the decision-making outcomes from those of standard approaches that ignore uncertainty in prevalence estimates.ResultsBy 2010, most regions in Somalia were at least 70% likely to be below 5% PfPR2-10 and, by 2014, 17 regions were below 5% PfPR2-10 with a probability greater than 90%. Larger uncertainty is observed using a threshold of 1%. By 2011, only two regions were more than 90% likely of being < 1% PfPR2-10 and, by 2014, only three regions showed such low level of uncertainty. The use of non-exceedance probabilities indicated that there was weak evidence to classify 10 out of the 18 regions as < 1% in 2014, when a greater than 90% non-exceedance probability was required.ConclusionUnlike standard approaches, non-exceedance probabilities of spatially modelled PfPR2-10 allow to quantify uncertainty of prevalence estimates in relation to policy relevant intervention thresholds, providing programmatically relevant metrics to make decisions on transitioning from sustained malaria control to strategies that encompass methods of malaria elimination.
| S-EPMC5819647 | biostudies-literature
Project description:Understanding the transmission dynamics of COVID-19 is crucial for evaluating its spread pattern, especially in metropolitan areas of China, as its spread could lead to secondary outbreaks. In addition, the experiences gained and lessons learned from China have the potential to provide evidence to support other metropolitan areas and large cities outside China with their emerging cases. We used data reported from January 24, 2020, to February 23, 2020, to fit a model of infection, estimate the likely number of infections in four high-risk metropolitan areas based on the number of cases reported, and increase the understanding of the COVID-19 spread pattern. Considering the effect of the official quarantine regulations and travel restrictions for China, which began January 23~24, 2020, we used the daily travel intensity index from the Baidu Maps app to roughly simulate the level of restrictions and estimate the proportion of the quarantined population. A group of SEIR model statistical parameters were estimated using Markov chain Monte Carlo (MCMC) methods and fitting on the basis of reported data. As a result, we estimated that the basic reproductive number, R0, was 2.91 in Beijing, 2.78 in Shanghai, 2.02 in Guangzhou, and 1.75 in Shenzhen based on the data from January 24, 2020, to February 23, 2020. In addition, we inferred the prediction results and compared the results of different levels of parameters. For example, in Beijing, the predicted peak number of cases was 467 with a peak time of March 01, 2020; however, if the city were to implement different levels (strict, moderate, or weak) of travel restrictions or regulation measures, the estimation results showed that the transmission dynamics would change and that the peak number of cases would differ by between 54% and 209%. We concluded that public health interventions would reduce the risk of the spread of COVID-19 and that more rigorous control and prevention measures would effectively contain its further spread, and awareness of prevention should be enhanced when businesses and social activities return to normal before the end of the epidemic. Further, the experiences gained and lessons learned from China offer the potential to provide evidence supporting other metropolitan areas and big cities with their emerging cases outside China.
| S-EPMC7221060 | biostudies-literature
Project description:During 2018, Heartland virus RNA was detected in an Amblyomma americanum tick removed from a resident of Suffolk County, New York, USA. The person showed seroconversion. Tick surveillance and white-tailed deer (Odocoileus virginianus) serosurveys showed widespread distribution in Suffolk County, emphasizing a need for disease surveillance anywhere A. americanum ticks are established or emerging.
| S-EPMC8632170 | biostudies-literature
Project description:BackgroundTuberculosis is an infectious bacterial disease that is spread via respiratory droplets from infected individuals to susceptible contacts. To eliminate this disease from low- and medium-incidence settings, people who are most likely to be infected (contacts) must be identified. Recently, study authors have examined alternate approaches to contact tracing methods that demonstrate improved detection and prioritization of contacts. The comparative benefit of these methods has not been established.ObjectivesTo assess the effectiveness of novel methods of contact tracing versus current standard of care to identify latent and active cases in low- to moderate-incidence settings.Search methodsWe searched CENTRAL, MEDLINE, Embase, LILACS, Web of Science, and CINAHL up to 15 July 2019. We also searched for clinical trials and examined reference lists and conference proceedings.Selection criteriaRandomized controlled trials (RCTs) and cluster-RCTs of contact tracing strategies that included alternate approaches (other than standard practice).Data collection and analysisTwo review authors independently assessed identified articles for eligibility and quality using prespecified criteria.Main resultsNo trials met the inclusion criteria of this review. Several study authors described an alternate method for examining contacts and performing social network analysis but did not compare this with the current contact tracing approach.Authors' conclusionsThis Cochrane Review highlights the lack of research in support of the current contact tracing method and the need for RCTs to compare new methods such as social network analysis to improve contact tracing processes.
| S-EPMC6713498 | biostudies-literature
Project description:A more sensitive surveillance tool is needed to identify Plasmodium vivax infections for treatment and to accelerate malaria elimination efforts. To address this challenge, our laboratory has developed an eight-antigen panel that detects total IgG as serological markers of P. vivax exposure within the prior 9 months. The value of these markers has been established for use in areas with low transmission. In moderate-high transmission areas, there is evidence that total IgG is more long-lived than in areas with low transmission, resulting in poorer performance of these markers in these settings. Antibodies that are shorter-lived may be better markers of recent infection for use in moderate-high transmission areas. Using a multiplex assay, the antibody temporal kinetics of total IgG, IgG1, IgG3, and IgM against 29 P. vivax antigens were measured over 36 weeks following asymptomatic P. vivax infection in Papua New Guinean children (n = 31), from an area with moderate-high transmission intensity. IgG3 declined faster to background than total IgG, IgG1, and IgM. Based on these kinetics, IgG3 performance was then assessed for classifying recent exposure in a cohort of Peruvian individuals (n = 590; age 3-85 years) from an area of moderate transmission intensity. Using antibody responses against individual antigens, the highest performance of IgG3 in classifying recent P. vivax infections in the prior 9 months was to one of the Pv-fam-a proteins assessed (PVX_125728) (AUC = 0.764). Surprisingly, total IgG was overall a better marker of recent P. vivax infection, with the highest individual classification performance to RBP2b1986-2653 (PVX_094255) (AUC = 0.838). To understand the acquisition of IgG3 in this Peruvian cohort, relevant epidemiological factors were explored using a regression model. IgG3 levels were positively associated with increasing age, living in an area with (relatively) higher transmission intensity, and having three or more PCR-detected blood-stage P. vivax infections within the prior 13 months. Overall, we found that IgG3 did not have high accuracy for detecting recent exposure to P. vivax in the Peruvian cohort, with our data suggesting that this is due to the high levels of prior exposure required to acquire high IgG3 antibody levels.
| S-EPMC9395743 | biostudies-literature
Project description:BackgroundIndividual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains.MethodsThe EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status.ResultsComparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.ConclusionWe observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.
| S-EPMC6121813 | biostudies-literature