Browsing by Subject "Disease Outbreaks"
Now showing 1 - 8 of 8
Results Per Page
Sort Options
Item Open Access Development of a TaqMan Array Card for Acute-Febrile-Illness Outbreak Investigation and Surveillance of Emerging Pathogens, Including Ebola Virus.(J Clin Microbiol, 2016-01) Liu, Jie; Ochieng, Caroline; Wiersma, Steve; Ströher, Ute; Towner, Jonathan S; Whitmer, Shannon; Nichol, Stuart T; Moore, Christopher C; Kersh, Gilbert J; Kato, Cecilia; Sexton, Christopher; Petersen, Jeannine; Massung, Robert; Hercik, Christine; Crump, John A; Kibiki, Gibson; Maro, Athanasia; Mujaga, Buliga; Gratz, Jean; Jacob, Shevin T; Banura, Patrick; Scheld, W Michael; Juma, Bonventure; Onyango, Clayton O; Montgomery, Joel M; Houpt, Eric; Fields, BarryAcute febrile illness (AFI) is associated with substantial morbidity and mortality worldwide, yet an etiologic agent is often not identified. Convalescent-phase serology is impractical, blood culture is slow, and many pathogens are fastidious or impossible to cultivate. We developed a real-time PCR-based TaqMan array card (TAC) that can test six to eight samples within 2.5 h from sample to results and can simultaneously detect 26 AFI-associated organisms, including 15 viruses (chikungunya, Crimean-Congo hemorrhagic fever [CCHF] virus, dengue, Ebola virus, Bundibugyo virus, Sudan virus, hantaviruses [Hantaan and Seoul], hepatitis E, Marburg, Nipah virus, o'nyong-nyong virus, Rift Valley fever virus, West Nile virus, and yellow fever virus), 8 bacteria (Bartonella spp., Brucella spp., Coxiella burnetii, Leptospira spp., Rickettsia spp., Salmonella enterica and Salmonella enterica serovar Typhi, and Yersinia pestis), and 3 protozoa (Leishmania spp., Plasmodium spp., and Trypanosoma brucei). Two extrinsic controls (phocine herpesvirus 1 and bacteriophage MS2) were included to ensure extraction and amplification efficiency. Analytical validation was performed on spiked specimens for linearity, intra-assay precision, interassay precision, limit of detection, and specificity. The performance of the card on clinical specimens was evaluated with 1,050 blood samples by comparison to the individual real-time PCR assays, and the TAC exhibited an overall 88% (278/315; 95% confidence interval [CI], 84% to 92%) sensitivity and a 99% (5,261/5,326, 98% to 99%) specificity. This TaqMan array card can be used in field settings as a rapid screen for outbreak investigation or for the surveillance of pathogens, including Ebola virus.Item Open Access Effective health communication - a key factor in fighting the COVID-19 pandemic.(Patient education and counseling, 2020-05) Finset, Arnstein; Bosworth, Hayden; Butow, Phyllis; Gulbrandsen, Pål; Hulsman, Robert L; Pieterse, Arwen H; Street, Richard; Tschoetschel, Robin; van Weert, JuliaItem Open Access Emergence and pathogenicity of highly virulent Cryptococcus gattii genotypes in the northwest United States.(PLoS Pathog, 2010-04-22) Byrnes 3rd, EJ; Li, W; Lewit, Y; Ma, H; Voelz, K; Ren, P; Carter, DA; Chaturvedi, V; Bildfell, RJ; May, RC; Heitman, JCryptococcus gattii causes life-threatening disease in otherwise healthy hosts and to a lesser extent in immunocompromised hosts. The highest incidence for this disease is on Vancouver Island, Canada, where an outbreak is expanding into neighboring regions including mainland British Columbia and the United States. This outbreak is caused predominantly by C. gattii molecular type VGII, specifically VGIIa/major. In addition, a novel genotype, VGIIc, has emerged in Oregon and is now a major source of illness in the region. Through molecular epidemiology and population analysis of MLST and VNTR markers, we show that the VGIIc group is clonal and hypothesize it arose recently. The VGIIa/IIc outbreak lineages are sexually fertile and studies support ongoing recombination in the global VGII population. This illustrates two hallmarks of emerging outbreaks: high clonality and the emergence of novel genotypes via recombination. In macrophage and murine infections, the novel VGIIc genotype and VGIIa/major isolates from the United States are highly virulent compared to similar non-outbreak VGIIa/major-related isolates. Combined MLST-VNTR analysis distinguishes clonal expansion of the VGIIa/major outbreak genotype from related but distinguishable less-virulent genotypes isolated from other geographic regions. Our evidence documents emerging hypervirulent genotypes in the United States that may expand further and provides insight into the possible molecular and geographic origins of the outbreak.Item Open Access From Hendra to Wuhan: what has been learned in responding to emerging zoonotic viruses.(Lancet (London, England), 2020-02) Wang, Lin-Fa; Anderson, Danielle E; Mackenzie, John S; Merson, Michael HItem Open Access Multiple models for outbreak decision support in the face of uncertainty.(Proceedings of the National Academy of Sciences of the United States of America, 2023-05) Shea, Katriona; Borchering, Rebecca K; Probert, William JM; Howerton, Emily; Bogich, Tiffany L; Li, Shou-Li; van Panhuis, Willem G; Viboud, Cecile; Aguás, Ricardo; Belov, Artur A; Bhargava, Sanjana H; Cavany, Sean M; Chang, Joshua C; Chen, Cynthia; Chen, Jinghui; Chen, Shi; Chen, YangQuan; Childs, Lauren M; Chow, Carson C; Crooker, Isabel; Del Valle, Sara Y; España, Guido; Fairchild, Geoffrey; Gerkin, Richard C; Germann, Timothy C; Gu, Quanquan; Guan, Xiangyang; Guo, Lihong; Hart, Gregory R; Hladish, Thomas J; Hupert, Nathaniel; Janies, Daniel; Kerr, Cliff C; Klein, Daniel J; Klein, Eili Y; Lin, Gary; Manore, Carrie; Meyers, Lauren Ancel; Mittler, John E; Mu, Kunpeng; Núñez, Rafael C; Oidtman, Rachel J; Pasco, Remy; Pastore Y Piontti, Ana; Paul, Rajib; Pearson, Carl AB; Perdomo, Dianela R; Perkins, T Alex; Pierce, Kelly; Pillai, Alexander N; Rael, Rosalyn Cherie; Rosenfeld, Katherine; Ross, Chrysm Watson; Spencer, Julie A; Stoltzfus, Arlin B; Toh, Kok Ben; Vattikuti, Shashaank; Vespignani, Alessandro; Wang, Lingxiao; White, Lisa J; Xu, Pan; Yang, Yupeng; Yogurtcu, Osman N; Zhang, Weitong; Zhao, Yanting; Zou, Difan; Ferrari, Matthew J; Pannell, David; Tildesley, Michael J; Seifarth, Jack; Johnson, Elyse; Biggerstaff, Matthew; Johansson, Michael A; Slayton, Rachel B; Levander, John D; Stazer, Jeff; Kerr, Jessica; Runge, Michael CPolicymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.Item Open Access The Metrics Matter: Improving Comparisons of COVID-19 Outbreaks in Nursing Homes.(Journal of the American Medical Directors Association, 2021-05) Miller, Katherine EM; Gorges, Rebecca J; Konetzka, R Tamara; Van Houtven, Courtney HObjectives
In the United States, nursing facility residents comprise fewer than 1% of the population but more than 40% of deaths due to Coronavirus Disease 2019 (COVID-19). Mitigating the enormous risk of COVID-19 to nursing home residents requires adequate data. The widely used Centers for Medicare & Medicaid Services (CMS) COVID-19 Nursing Home Dataset contains 2 derived statistics: Total Resident Confirmed COVID-19 Cases per 1000 Residents and Total Resident COVID-19 Deaths per 1000 Residents. These metrics provide a misleading picture, as facilities report cumulative counts of cases and deaths over different time periods but use a point-in-time measure as proxy for number of residents (number of occupied beds in a week), resulting in inflated statistics. We propose an alternative statistic to better illustrate the burden of COVID-19 cases and deaths across nursing facilities.Design
Retrospective cohort study.Setting and participants
Using the CMS Nursing Home Compare and COVID-19 Nursing Home Datasets, we examined facilities with star ratings and COVID-19 data passing quality assurance checks for each reporting period from May 31 to August 16, 2020 (n = 11,115).Methods
We derived an alternative measure of the number of COVID-19 cases per 1000 residents using the net change in weekly census. For each measure, we compared predicted number of cases/deaths by overall star rating using negative binomial regression with constant dispersion, controlling for county-level cases per capita and nursing home characteristics.Results
The average number of cases per 1000 estimated residents using our method is lower compared with the metric using occupied beds as proxy for number of residents (44.8 compared with 66.6). We find similar results when examining number of COVID-19 deaths per 1000 residents.Conclusions and implications
Future research should estimate the number of residents served in nursing facilities when comparing COVID-19 cases/deaths in nursing facilities. Identifying appropriate metrics for facility-level comparisons is critical to protecting nursing home residents as the pandemic continues.Item Open Access Transmission roles of symptomatic and asymptomatic COVID-19 cases: a modelling study.(Epidemiology and infection, 2022-09) Tan, Jianbin; Ge, Yang; Martinez, Leonardo; Sun, Jimin; Li, Changwei; Westbrook, Adrianna; Chen, Enfu; Pan, Jinren; Li, Yang; Cheng, Wei; Ling, Feng; Chen, Zhiping; Shen, Ye; Huang, HuiCoronavirus disease 2019 (COVID-19) asymptomatic cases are hard to identify, impeding transmissibility estimation. The value of COVID-19 transmissibility is worth further elucidation for key assumptions in further modelling studies. Through a population-based surveillance network, we collected data on 1342 confirmed cases with a 90-days follow-up for all asymptomatic cases. An age-stratified compartmental model containing contact information was built to estimate the transmissibility of symptomatic and asymptomatic COVID-19 cases. The difference in transmissibility of a symptomatic and asymptomatic case depended on age and was most distinct for the middle-age groups. The asymptomatic cases had a 66.7% lower transmissibility rate than symptomatic cases, and 74.1% (95% CI 65.9-80.7) of all asymptomatic cases were missed in detection. The average proportion of asymptomatic cases was 28.2% (95% CI 23.0-34.6). Simulation demonstrated that the burden of asymptomatic transmission increased as the epidemic continued and could potentially dominate total transmission. The transmissibility of asymptomatic COVID-19 cases is high and asymptomatic COVID-19 cases play a significant role in outbreaks.Item Open Access Whole genome sequencing identifies circulating Beijing-lineage Mycobacterium tuberculosis strains in Guatemala and an associated urban outbreak.(Tuberculosis (Edinb), 2015-12) Saelens, Joseph W; Lau-Bonilla, Dalia; Moller, Anneliese; Medina, Narda; Guzmán, Brenda; Calderón, Maylena; Herrera, Raúl; Sisk, Dana M; Xet-Mull, Ana M; Stout, Jason E; Arathoon, Eduardo; Samayoa, Blanca; Tobin, David MLimited data are available regarding the molecular epidemiology of Mycobacterium tuberculosis (Mtb) strains circulating in Guatemala. Beijing-lineage Mtb strains have gained prevalence worldwide and are associated with increased virulence and drug resistance, but there have been only a few cases reported in Central America. Here we report the first whole genome sequencing of Central American Beijing-lineage strains of Mtb. We find that multiple Beijing-lineage strains, derived from independent founding events, are currently circulating in Guatemala, but overall still represent a relatively small proportion of disease burden. Finally, we identify a specific Beijing-lineage outbreak centered on a poor neighborhood in Guatemala City.