Browsing by Subject "Epidemiological Monitoring"

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    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, Barry
    Acute 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.
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    Ecology and economics for pandemic prevention.
    (Science (New York, N.Y.), 2020-07) Dobson, Andrew P; Pimm, Stuart L; Hannah, Lee; Kaufman, Les; Ahumada, Jorge A; Ando, Amy W; Bernstein, Aaron; Busch, Jonah; Daszak, Peter; Engelmann, Jens; Kinnaird, Margaret F; Li, Binbin V; Loch-Temzelides, Ted; Lovejoy, Thomas; Nowak, Katarzyna; Roehrdanz, Patrick R; Vale, Mariana M
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    Estimating leptospirosis incidence using hospital-based surveillance and a population-based health care utilization survey in Tanzania.
    (PLoS Negl Trop Dis, 2013) Biggs, Holly M; Hertz, Julian T; Munishi, O Michael; Galloway, Renee L; Marks, Florian; Saganda, Wilbrod; Maro, Venance P; Crump, John A
    BACKGROUND: The incidence of leptospirosis, a neglected zoonotic disease, is uncertain in Tanzania and much of sub-Saharan Africa, resulting in scarce data on which to prioritize resources for public health interventions and disease control. In this study, we estimate the incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a population-based household health care utilization survey in two districts in the Kilimanjaro Region of Tanzania and identified leptospirosis cases at two hospital-based fever sentinel surveillance sites in the Kilimanjaro Region. We used multipliers derived from the health care utilization survey and case numbers from hospital-based surveillance to calculate the incidence of leptospirosis. A total of 810 households were enrolled in the health care utilization survey and multipliers were derived based on responses to questions about health care seeking in the event of febrile illness. Of patients enrolled in fever surveillance over a 1 year period and residing in the 2 districts, 42 (7.14%) of 588 met the case definition for confirmed or probable leptospirosis. After applying multipliers to account for hospital selection, test sensitivity, and study enrollment, we estimated the overall incidence of leptospirosis ranges from 75-102 cases per 100,000 persons annually. CONCLUSIONS/SIGNIFICANCE: We calculated a high incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania, where leptospirosis incidence was previously unknown. Multiplier methods, such as used in this study, may be a feasible method of improving availability of incidence estimates for neglected diseases, such as leptospirosis, in resource constrained settings.
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    Evaluating Response Time in Zanzibar's Malaria Elimination Case-Based Surveillance-Response System.
    (The American journal of tropical medicine and hygiene, 2019-02) Khandekar, Eeshan; Kramer, Randall; Ali, Abdullah S; Al-Mafazy, Abdul-Wahid; Egger, Joseph R; LeGrand, Sara; Mkali, Humphrey R; McKay, Michael; Ngondi, Jeremiah M
    As countries transition toward malaria elimination, malaria programs rely on surveillance-response systems, which are often supported by web- and mobile phone-based reporting tools. Such surveillance-response systems are interventions for elimination, making it important to determine if they are operating optimally. A metric to measure this by is timeliness. This study used a mixed-methods approach to investigate the response time of Zanzibar's malaria elimination surveillance-response system, Malaria Case Notification (MCN). MCN conducts both passive and reactive case detection, supported by a mobile phone-based reporting tool called Coconut Surveillance. Using data obtained from RTI International and the Zanzibar Malaria Elimination Program (ZAMEP), analysis of summary statistics was conducted to investigate the association of response time with geography, and time series techniques were used to investigate trends in response time and its association with the number of reported cases. Results indicated that response time varied by the district in Zanzibar (0.6-6.05 days) and that it was not associated with calendar time or the number of reported cases. Survey responses and focus groups with a cadre of health workers, district malaria surveillance officers, shed light on operational challenges faced during case investigation, such as incomplete health records and transportation issues, which stem from deficiencies in aspects of ZAMEP's program management. These findings illustrate that timely response for malaria elimination depends on effective program management, despite the automation of web-based or mobile phone-based tools. For surveillance-response systems to work optimally, malaria programs should ensure that optimal management practices are in place.