Early Detection of Pandemic (H1N1) 2009, Bangladesh

Azziz‐Baumgartner, Eduardo; Rahman, Mustafizur; Mamun, Abdullah Al; Haider, Mohammad Sabbir; Zaman, Rashid Uz; Karmakar, Polash Chandra; Nasreen, Sharifa; Muneer, Syeda Mah-E; Homaira, Nusrat; Goswami, Doli; Ahmed, Be-Nazir; Husain, Mohammad Mushtuq; Jamil, Khondokar Mahbuba; Khatun, Selina; Ahmed, Mujaddeed; Chakraborty, Apurba; Fry, Alicia M.; Widdowson, Marc‐Alain; Bresee, Joseph S.; Azim, Tasnim; Alamgir, A. S. M.; Brooks, Abdullah; Hossain, M. J.; Klimov, Alexander; Rahman, Mahmudur; Luby, Stephen P.

doi:10.3201/eid1801.101996

Cited by 11 publications

(10 citation statements)

References 5 publications

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“…There is increasing recognition of the value of novel data sources to improve the sensitivity of infectious disease surveillance, some of which can provide crucial information in remote areas [20]. Novel approaches include surveillance for media reports of disease clusters, as used for various infectious diseases in Bangladesh [12,28], and training of local drug sellers to recognize and report disease symptoms, as rolled out nationally to enhance tuberculosis surveillance in Ghana [29]. Other surveillance data streams, such as monitoring over-the-counter medication sales, telephone triage, and webbased queries, have been successfully integrated in surveillance systems in resource-rich settings [30].…”

Section: Discussionmentioning

confidence: 99%

Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data

et al. 2017

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BackgroundThe International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements.Methods and FindingsWe propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals.We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented.Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and surveillance resources.ConclusionWe present a new approach to evaluating the sensitivity and representativeness of hospital-based surveillance, making it possible to predict its ability to detect emerging threats.

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Section: Discussionmentioning

confidence: 99%

Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data

et al. 2017

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“…For longer delays, the range of prophylaxis waste expands to higher treatment coverages ( Figure 3d–f ). The overall waste of prophylaxis is significantly higher in the model with the original RC demographics compared to SD, and could be as much as 3 times higher in the range 10%–40% treatment coverage, which is considered a plausible range for public health to successfully implement an antiviral treatment policy [20] , [21] . This relatively low treatment coverage may result from several factors, including diagnosis uncertainties for influenza cases, treatment guidelines for use of antiviral drugs, familiarity with antiviral agents, access to drug stockpiles, or knowledge of the potential severity and outcomes of infection.…”

Section: Resultsmentioning

confidence: 99%

Antiviral Strategies for Emerging Influenza Viruses in Remote Communities

2014

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BackgroundDue to the lack of timely access to resources for critical care, strategic use of antiviral drugs is crucial for mitigating the impact of novel influenza viruses with pandemic potential in remote and isolated communities. We sought to evaluate the effect of antiviral treatment and prophylaxis of close contacts in a Canadian remote northern community.MethodsWe used an agent-based, discrete-time simulation model for disease spread in a remote community, which was developed as an in-silico population using population census data. Relative and cumulative age-specific attack rates, and the total number of infections in simulated model scenarios were obtained.ResultsWe found that early initiation of antiviral treatment is more critical for lowering attack rates in a remote setting with a low population-average age compared to an urban population. Our results show that a significant reduction in the relative, age-specific attack rates due to increasing treatment coverage does not necessarily translate to a significant reduction in the overall arrack rate. When treatment coverage varies from low to moderate, targeted prophylaxis has a very limited impact in reducing attack rates and should be offered at a low level (below 10%) to avoid excessive waste of drugs.ConclusionsIn contrast to previous work, for conservative treatment coverages, our results do not provide any convincing evidence for the implementation of targeted prophylaxis. The findings suggest that public health strategies in remote communities should focus on the wider availability (higher coverage) and timely distribution of antiviral drugs for treatment of clinically ill individuals.

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“…The value of routine surveillance capacity in supporting demands placed on systems during pandemics aligns with previous reports that showed significant progress in core capabilities for influenza pandemic preparedness among the same countries ( 5 , 6 ). In Bangladesh, enhanced surveillance of laboratory-confirmed pH1N1 infection facilitated a response weeks before the spread to the general population ( 21 ). In the African region, several countries were able to show the first introduction of pH1N1 virus within their countries ( 22 , 23 ).…”

Section: Discussionmentioning

confidence: 99%