Under-detection of blood culture-positive enteric fever cases: The impact of missing data and methods for adjusting incidence estimates

Voysey, Merryn; Pant, Dikshya; Shakya, Mila; Liu, Xinxue; Colin-Jones, Rachel; Theiss-Nyland, Katherine; Smith, N.; Shrestha, Shrijana; Basnyat, Buddha; Pollard, Andrew J.; Pitzer, Virginia E.

doi:10.1371/journal.pntd.0007805

Cited by 19 publications

(20 citation statements)

References 11 publications

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“…The epidemics of MDR typhoid in several countries in the 1980s and 1990s were the driving force for making ciprofloxacin the drug of choice for the treatment of typhoid [ 22 , 24 , 25 ]. Fluoroquinolone non-susceptibility in S .…”

Section: Discussionmentioning

confidence: 99%

“…The probability of sending a blood culture for diagnosis depends on multiple factors: duration of fever, presence or absence of signs and symptoms of other diseases, and prior antibiotic use. These factors, coupled with limited availability of facilities for blood culture, leads to underreporting of the true number of cases of blood culture-confirmed typhoid [ 24 , 25 ].…”

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confidence: 99%

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Antimicrobial Resistance in Typhoidal Salmonella: Surveillance for Enteric Fever in Asia Project, 2016–2019

Qamar

Yousafzai

Dehraj

et al. 2020

Clinical Infectious Diseases

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Background Clinicians have limited therapeutic options for enteric as a result of increasing antimicrobial resistance, and therefore typhoid vaccination is recommended as a preventive measure. As a part of the Surveillance for Enteric Fever in Asia Project (SEAP), we investigated the extent measured the burden of antimicrobial resistance (AMR) among confirmed enteric fever cases in Bangladesh, Nepal, and Pakistan. Methods From September 2016–September 2019, SEAP recruited study participants of all age groups from its outpatient, inpatient, hospital laboratory, laboratory network, and surgical sites who had a diagnosis of febrile illness that was either suspected or blood culture confirmed for enteric fever. Antimicrobial resistance of isolates was determined by disc diffusion using Clinical and Laboratory Standard Institute cut-off points. We reported the frequency of multidrug resistance (MDR)(resistance to ampicillin, cotrimoxazole, and chloramphenicol), extensive drug resistance (XDR) (MDR plus non-susceptible to fluoroquinolone and any 3rd generation cephalosporins), and fluoroquinolone (FQ) and azithromycin non-susceptibility. Results We enrolled 8,705 blood culture confirmed enteric fever cases: 4,873 (56%) from Bangladesh, 1,602 (18%) from Nepal and 2,230 (26%) from Pakistan. Of these, 7,591 (87%) were Salmonella Typhi and 1114 (13%) were S. Paratyphi. MDR S. Typhi was identified in 17% (701/4065) of isolates in Bangladesh, and 1% (19/1342) in Nepal. In Pakistan, 16 % (331/2084) of S. Typhi isolates were MDR, and 64% (1319/2074) were XDR. FQ nonsusceptibility among S. Typhi isolates was 98% in Bangladesh, 87% in Nepal, and 95% in Pakistan. Azithromycin non-susceptibility was detected in 77 (2%) in Bangladesh, 9 (.67%) in Nepal and 9 (.59%) isolates in Pakistan. In Pakistan, three (2%) S. Paratyphi isolates were MDR; no MDR S. Paratyphi was reported from Bangladesh or Nepal. Conclusions Although AMR against S. Paratyphi was low across the three countries, there was widespread drug resistance among S. Typhi, including FQ non-susceptibility and the emergence of XDR S. Typhi in Pakistan, limiting treatment options. As typhoid conjugate vaccine (TCV) is rolled out, surveillance should continue to monitor changes in AMR to inform policies and to monitor drug resistance in S. Paratyphi, for which there is no vaccine.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Antimicrobial Resistance in Typhoidal Salmonella: Surveillance for Enteric Fever in Asia Project, 2016–2019

Qamar

Yousafzai

Dehraj

et al. 2020

Clinical Infectious Diseases

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“…Each study employs an adjustment for blood culture sensitivity, but STRATAA samples from probability distributions informed by a recent meta-analysis of blood culture sensitivity by volume of blood acquired per subject and reported prior antibiotic usage [ 25 ], whereas SEAP and SETA apply the same correction factor (assuming sensitivity of 59%) to each blood culture result [ 26 ]. For the healthcare-seeking adjustment, SETA assumes the same risk of typhoid infection for patients who seek care at a study facility and for patients who seek care elsewhere, whereas SEAP, SEFI tier 2, and STRATAA assume a differential typhoid risk for febrile patients who seek care at a study facility [ 13 , 27 ]. SEFI tier 1 does not include a healthcare-seeking adjustment, since it employs active surveillance.…”

Section: Discussionmentioning

confidence: 99%

The Surveillance for Enteric Fever in Asia Project (SEAP), Severe Typhoid Fever Surveillance in Africa (SETA), Surveillance of Enteric Fever in India (SEFI), and Strategic Typhoid Alliance Across Africa and Asia (STRATAA) Population-based Enteric Fever Studies: A Review of Methodological Similarities and Differences

Carey

MacWright²,

et al. 2020

Clinical Infectious Diseases

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Building on previous multicountry surveillance studies of typhoid and others salmonelloses such as the Diseases of the Most Impoverished program and the Typhoid Surveillance in Africa Project, several ongoing blood culture surveillance studies are generating important data about incidence, severity, transmission, and clinical features of invasive Salmonella infections in sub-Saharan Africa and South Asia. These studies are also characterizing drug resistance patterns in their respective study sites. Each study answers a different set of research questions and employs slightly different methodologies, and the geographies under surveillance differ in size, population density, physician practices, access to healthcare facilities, and access to microbiologically safe water and improved sanitation. These differences in part reflect the heterogeneity of the epidemiology of invasive salmonellosis globally, and thus enable generation of data that are useful to policymakers in decision-making for the introduction of typhoid conjugate vaccines (TCVs). Moreover, each study is evaluating the large-scale deployment of TCVs, and may ultimately be used to assess post-introduction vaccine impact. The data generated by these studies will also be used to refine global disease burden estimates. It is important to ensure that lessons learned from these studies not only inform vaccination policy, but also are incorporated into sustainable, low-cost, integrated vaccine-preventable disease surveillance systems.

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“…Baseline information on eligible patients presenting to fever surveillance facilities was recorded both for those who did, and those who did not, have blood drawn for culture. Based on the analysis of these data in the TyVAC population in Nepal, the relative risk of blood culture positivity ( R B ) was 1.87 times higher (95% CI: 0.9-3.9) among those who received a blood culture compared to those who did not [10]. Thus, the overall probability of receiving a blood culture is the sum of the proportion of individuals who received a blood culture plus the quotient of the proportion of those who did not receive a blood culture divided by the relative risk of blood culture positivity ( R B ).…”

Section: Methodsmentioning

confidence: 99%

“…Diagnostic tests can be invasive, and parents or guardians of young children sometimes do not want their children to have large amounts of blood drawn when they are already ill. In resource-poor countries in particular, lack of supplies and personnel lead to long wait times for receiving healthcare, further adding to lower rates of confirmatory testing, and clinical opinion on the cause of fever can also affect the likelihood of blood being drawn for culture [10].…”

Section: Introductionmentioning

confidence: 99%

A Bayesian approach for estimating typhoid fever incidence from large-scale facility-based passive surveillance data

Phillips

Meiring

Voysey

et al. 2020

Preprint

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Background. Decisions about typhoid fever prevention and control are based on current estimates of typhoid incidence and their uncertainty, which can be difficult to measure. Limits of using facility-based estimates alone- the lack of specific clinical diagnostic criteria, poorly sensitive and specific diagnostic tests, and scarcity of accurate and complete datasets- contribute to difficulties in calculating population-level incidence of typhoid. Methods. Using data from the Strategic Alliance across Africa & Asia (STRATAA) programme, we integrated information from demographic censuses, healthcare utilization surveys, facility-based passive surveillance, and serological surveillance from sites in Malawi, Nepal, and Bangladesh in order to adjust crude incidence estimates to account for under-detection. We developed an approach using a Bayesian framework that adjusts the count of reported blood-culture-positive cases of typhoid for each of the following phases: healthcare seeking, blood culture collection, and blood culture detection. We estimated the proportion of "true" typhoid cases occurring in the population under surveillance captured at each phase by combining information from the observed cases from the STRATAA datasets and estimates from prior published studies. We confirmed that the model was correctly formulated by comparing to simulated data. Results. The ratio between the observed and adjusted incidence rates was 8.2 (95% CI: 6.4-13.3) in Malawi, 13.8 (95% CI: 8.8-23.0) in Nepal, and 7.0 (95% CI: 5.5-9.1) in Bangladesh, and varied by age across the three sites. The probability of having blood drawn for culture led to the largest adjustment in Malawi, while the probability of seeking healthcare contributed the most to adjustment factors in Nepal and Bangladesh. Adjusted incidence rates were mostly within the limits of the seroincidence rate of typhoid infection determined by serological data. Conclusion. Passive surveillance of blood culture-confirmed typhoid fever without adjustment for case ascertainment, sample collection and diagnostic sensitivity results in considerable underestimation of the true incidence of typhoid in the population. Our approach allows each phase of the typhoid reporting process to be synthesized to estimate the adjusted incidence of typhoid fever while correctly characterizing uncertainty in this estimate, which can inform decision-making for typhoid prevention and control.

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Under-detection of blood culture-positive enteric fever cases: The impact of missing data and methods for adjusting incidence estimates

Cited by 19 publications

References 11 publications

Antimicrobial Resistance in Typhoidal Salmonella: Surveillance for Enteric Fever in Asia Project, 2016–2019

Antimicrobial Resistance in Typhoidal Salmonella: Surveillance for Enteric Fever in Asia Project, 2016–2019

A Bayesian approach for estimating typhoid fever incidence from large-scale facility-based passive surveillance data

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