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

Informing an investment case for Japanese encephalitis vaccine introduction in Bangladesh

Japanese encephalitis virus (JEV) is a major threat to human health. Bangladesh is considering introducing a JEV vaccine; however, the investment case is hampered by a limited understanding of key aspects of JEV ecology. We conducted a seroprevalence study in a high-incidence region using an assay that limits cross-reactivity with dengue virus. We also trapped mosquitoes and collected information about potential host species. We used mathematical models to recover risk factors for infection and underlying probabilities of severe disease and death. We observed 19.0% [95% confidence interval (CI):17.1 to 21.1] of JEV antibodies. On average, 0.7% (95% CI: 0.2 to 2.0) of the susceptible population gets infected yearly, with pig proximity being the main human infection risk factor. Our traps captured 10 different mosquito species that have been linked with JEV transmission. We estimated that 1 in 1000 infections results in severe disease, 1 in 10,000 results in death, and 76% of severe cases are missed by surveillance.

Lessons learned from identifying clusters of severe acute respiratory infections with influenza sentinel surveillance, Bangladesh, 2009-2020

Background

We explored whether hospital-based surveillance is useful in detecting severe acute respiratory infection (SARI) clusters and how often these events result in outbreak investigation and community mitigation.

Methods

During May 2009-December 2020, physicians at 14 sentinel hospitals prospectively identified SARI clusters (i.e., ≥2 SARI cases who developed symptoms ≤10 days of each other and lived <30 min walk or <3 km from each other). Oropharyngeal and nasopharyngeal swabs were tested for influenza and other respiratory viruses by real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We describe the demographic of persons within clusters, laboratory results, and outbreak investigations.

Results

Field staff identified 464 clusters comprising 1427 SARI cases (range 0-13 clusters per month). Sixty percent of clusters had three, 23% had two, and 17% had ≥4 cases. Their median age was 2 years (inter-quartile range [IQR] 0.4-25) and 63% were male. Laboratory results were available for the 464 clusters with a median of 9 days (IQR = 6-13 days) after cluster identification. Less than one in five clusters had cases that tested positive for the same virus: respiratory syncytial virus (RSV) in 58 (13%), influenza viruses in 24 (5%), human metapneumovirus (HMPV) in five (1%), human parainfluenza virus (HPIV) in three (0.6%), adenovirus in two (0.4%). While 102/464 (22%) had poultry exposure, none tested positive for influenza A (H5N1) or A (H7N9). None of the 464 clusters led to field deployments for outbreak response.

Conclusions

For 11 years, none of the hundreds of identified clusters led to an emergency response. The value of this event-based surveillance might be improved by seeking larger clusters, with stronger epidemiologic ties or decedents.

Leaving no disease behind: The roadmap to securing universal health security and what this means for the surveillance of infectious diseases in Ghana as a precedent for sub-Saharan Africa

INTRODUCTION

Ghana is the first country in sub-Saharan Africa (SSA) to aim for universal health coverage (UHC). Based on Ghana's UHC system, the accessibility and distribution of healthcare facilities were evaluated for 2020. Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. Ghana as a precedent for SSA was evaluated and proposed to "leave no disease behind" in the surveillance of infectious diseases (IDs). This is to reinforce the sustainable development goals (SDG) 3 agenda on health that underpins monitoring equity in "leaving no one behind."

METHODS

Geospatial accessibility, travel time data, and algorithms were employed to evaluate the universality and accessibility of healthcare facilities, and their future projections to meet UHC by 2030. Healthcare facilities as surveillance sites were compared to community-based surveillance to identify which would be more applicable as a surveillance system to leave no disease behind in Ghana.

FINDINGS

Ghana has 93.8%, 6.1% and 0.1% as primary, secondary and tertiary healthcare facilities respectively. It has 26.1% of healthcare facilities remaining to meet the SDG 3 health target by 2030. In terms of providing quality healthcare, 29.3% and 67.2% of the additional required healthcare facilities for optimal allocation and achieving the UHC target need to be secondary and tertiary respectively. In assessing the broad spectrum of IDs studied from 2000 to 2020, an average of 226 IDs were endemic or potentially endemic to Ghana. The majority of the studies carried out to identify these IDs were done through community-based surveillance.

CONCLUSION

Establishing community-based surveillance sites to leave no disease behind and also providing the required healthcare facilities to reinforce leaving no one behind will enhance the universal health security of Ghana as a precedent for SSA.

Individual, household and community drivers of dengue virus infection risk in Kamphaeng Phet province, Thailand

Dengue virus (DENV) often circulates endemically. In such settings with high levels of transmission, it remains unclear whether there are risk factors that alter individual infection risk. We tested blood taken from individuals living in multigenerational households in Kamphaeng Phet province, Thailand for DENV antibodies (N = 2364, mean age 31y). Seropositivity ranged from 45.4% among those 1-5y to 99.5% for those >30y. Using spatially explicit catalytic models, we estimated 11.8% of the susceptible population gets infected annually. We found 37.5% of the variance in seropositivity was explained by unmeasured household-level effects with only 4.2% explained by spatial differences between households. The serostatus of individuals from the same household remained significantly correlated even when separated by up to 15 years in age. These findings show that despite highly endemic transmission, persistent differences in infection risk exist across households, the reasons for which remain unclear.

Clinical Cholera Surveillance Sensitivity in Bangladesh and Implications for Large-Scale Disease Control

Background

A surveillance system that is sensitive to detecting high burden areas is critical for achieving widespread disease control. In 2014, Bangladesh established a nationwide, facility-based cholera surveillance system for Vibrio cholerae infection. We sought to measure the sensitivity of this surveillance system to detect cases to assess whether cholera elimination targets outlined by the Bangladesh national control plan can be adequately measured.

Methods

We overlaid maps of nationally representative annual V cholerae seroincidence onto maps of the catchment areas of facilities where confirmatory laboratory testing for cholera was conducted, and we identified its spatial complement as surveillance greyspots, areas where cases likely occur but go undetected. We assessed surveillance system sensitivity and changes to sensitivity given alternate surveillance site selection strategies.

Results

We estimated that 69% of Bangladeshis (111.7 million individuals) live in surveillance greyspots and that 23% (25.5 million) of these individuals live in areas with the highest V cholerae infection rates.

Conclusions

The cholera surveillance system in Bangladesh has the ability to monitor progress towards cholera elimination goals among 31% of the country’s population, which may be insufficient for accurately measuring progress. Increasing surveillance coverage, particularly in the highest risk areas, should be considered.

Time-aggregated mobile phone mobility data are sufficient for modelling influenza spread: the case of Bangladesh

Human mobility plays a major role in the spatial dissemination of infectious diseases. We develop a spatio-temporal stochastic model for influenza-like disease spread based on estimates of human mobility. The model is informed by mobile phone mobility data collected in Bangladesh. We compare predictions of models informed by daily mobility data (reference) with that of models informed by time-averaged mobility data, and mobility model approximations. We find that the gravity model overestimates the spatial synchrony, while the radiation model underestimates the spatial synchrony. Using time-averaged mobility resulted in spatial spreading patterns comparable to the daily mobility model. We fit the model to 2014–2017 influenza data from sentinel hospitals in Bangladesh, using a sequential version of approximate Bayesian computation. We find a good agreement between our estimated model and the case data. We estimate transmissibility and regional spread of influenza in Bangladesh, which are useful for policy planning. Time-averaged mobility appears to be a good proxy for human mobility when modelling infectious diseases. This motivates a more general use of the time-averaged mobility, with important implications for future studies and outbreak control. Moreover, time-averaged mobility is subject to less privacy concerns than daily mobility, containing less temporal information on individual movements.

Comparing insights from clinic-based versus community-based outbreak investigations: a case study of chikungunya in Bangladesh

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A healthcare facility-based investigation of an outbreak would have been limited.

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Clinic-based case identification in this chikungunya outbreak would only have identified a quarter of all cases.

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Community-based household investigation involving only case households revealed that cases were more likely to be female and had lower educational attainment.

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Community-based investigation involving all households additionally identified clothing that exposed both limbs and traveling outside the district as risk factors.

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Outbreak investigations that identify cases in community and enroll controls from across the community should be used for better understanding of the risk factors as well as community transmission estimates.

Background

Outbreak investigations typically focus their efforts on identifying cases that present at healthcare facilities. However, these cases rarely represent all cases in the wider community. In this context, community-based investigations may provide additional insight into key risk factors for infection, however, the benefits of these more laborious data collection strategies remains unclear.

Methods

We used different subsets of the data from a comprehensive outbreak investigation to compare the inferences we make in alternative investigation strategies.

Results

The outbreak investigation team interviewed 1,933 individuals from 460 homes. 364 (18%) of individuals had symptoms consistent with chikungunya. A theoretical clinic-based study would have identified 26% of the cases. Adding in community-based cases provided an overall estimate of the attack rate in the community. Comparison with controls from the same household revealed that those with at least secondary education had a reduced risk. Finally, enrolling residents from households across the community allowed us to characterize spatial heterogeneity of risk and identify the type of clothing usually worn and travel history as risk factors. This also revealed that household-level use of mosquito control was not associated with infection.

Conclusions

These findings highlight that while clinic-based studies may be easier to conduct, they only provide limited insight into the burden and risk factors for disease. Enrolling people who escaped from infection, both in the household and in the community allows a step change in our understanding of the spread of a pathogen and maximizes opportunities for control.

Using healthcare-seeking behaviour to estimate the number of Nipah outbreaks missed by hospital-based surveillance in Bangladesh

BACKGROUND

Understanding the true burden of emergent diseases is critical for assessing public-health impact. However, surveillance often relies on hospital systems that only capture a minority of cases. We use the example of Nipah-virus infection in Bangladesh, which has a high case-fatality ratio and frequent person-to-person transmission, to demonstrate how healthcare-seeking data can estimate true burden.

METHODS

We fit logistic-regression models to data from a population-based, healthcare-seeking study of encephalitis cases to characterize the impact of distance and mortality on attending one of three surveillance hospital sites. The resulting estimates of detection probabilities, as a function of distance and outcome, are applied to all observed Nipah outbreaks between 2007 and 2014 to estimate the true burden.

RESULTS

The probability of attending a surveillance hospital fell from 82% for people with fatal encephalitis living 10 km away from a surveillance hospital to 54% at 50 km away. The odds of attending a surveillance hospital are 3.2 (95% confidence interval: 1.6, 6.6) times greater for patients who eventually died (i.e. who were more severely ill) compared with those who survived. Using these probabilities, we estimated that 119 Nipah outbreaks (95% confidence interval: 103, 140)-an average of 15 outbreaks per Nipah season-occurred during 2007-14; 62 (52%) were detected.

CONCLUSIONS

Our findings suggest hospital-based surveillance missed nearly half of all Nipah outbreaks. This analytical method allowed us to estimate the underlying burden of disease, which is important for emerging diseases where healthcare access may be limited.

Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India

Systematically collected hospitalization records provide valuable insight into disease patterns and support comprehensive national infectious disease surveillance networks. Hospitalization records detailing patient's place of residence (PoR) can be utilized to better understand a hospital's case load and strengthen surveillance among mobile populations. This study examined geographic patterns of patients treated for cholera at a major hospital in south India. We abstracted 1401 laboratory-confirmed cases of cholera between 2000-2014 from logbooks and electronic health records (EHRs) maintained by the Christian Medical College (CMC) in Vellore, Tamil Nadu, India. We constructed spatial trend models and identified two distinct clusters of patient residence-one around Vellore (836 records (61.2%)) and one in Bengal (294 records (21.5%)). We further characterized differences in peak timing and disease trend among these clusters to identify differences in cholera exposure among local and visiting populations. We found that the two clusters differ by their patient profiles, with patients in the Bengal cluster being most likely older males traveling to Vellore. Both clusters show well-aligned seasonal peaks in mid-July, only one week apart, with similar downward trend and proportion of predominant O1 serotype. Large hospitals can thus harness EHRs for surveillance by utilizing patients' PoRs to study disease patterns among resident and visitor populations.

Case-Fatality Ratio of Blood Culture-Confirmed Typhoid Fever in Dhaka, Bangladesh

With impending rollout of new conjugate typhoid vaccines, better estimates of typhoid case-fatality ratio are needed for countries to set priorities for public health programs. We enrolled 1425 patients of all ages with blood culture-confirmed Salmonella Typhi from laboratory networks serving inpatients and outpatients in Dhaka, Bangladesh. Participants were asked about symptoms and complications including death experienced over a median 3-month period following blood culture diagnosis. Four fatal cases were identified (case-fatality ratio of 0.3% [95% confidence interval, .05%-.55%]). Applying this case-fatality ratio to global typhoid burden estimates would reduce deaths by 70%.

Hospital-based zoonotic disease surveillance in Bangladesh: design, field data and difficulties

Early detection of zoonotic diseases allows for the implementation of early response measures, reducing loss of human life and economic disruption. We implemented a surveillance system in hospitals in Bangladesh to screen acutely ill hospitalized patients with severe respiratory infection and meningoencephalitis for zoonotic exposures. Patients were screened for the risk of zoonotic exposures with five questions covering vocational exposures, sick domestic animal and wild animal contact, and date palm sap consumption in the three weeks preceding illness onset. Patients giving at least one positive response were considered a potential zoonotic exposure. From September 2013 to March 2017, a total of 11 429 hospitalized patients across 14 participating hospitals were screened for exposures. Overall, 2% of patients reported a potential zoonotic exposure in the three-week period prior to becoming ill. Sixteen per cent of hospitalized patients with reported exposures died. After routine surveillance diagnostic testing, 88% of patients admitted to the hospital after a potential zoonotic exposure did not have a laboratory diagnosed aetiology for their illness. Hospital-based surveillance systems such as the Bangladeshi example presented here could play an important future role in the early detection of zoonotic spillover diseases. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Health facility preparedness for cholera outbreak response in four cholera-prone districts in Cameroon: a cross sectional study

BACKGROUND

The risk of cholera outbreak remains high in Cameroon. This is because of the persistent cholera outbreaks in neighboring countries coupled with the poor hygiene and sanitation conditions in Cameroon. The objective of this study was to assess the readiness of health facilities to respond to cholera outbreak in four cholera-prone districts in Cameroon.

METHODOLOGY

A cross-sectional study was conducted targeting all health facilities in four health districts, labeled as cholera hotspots in Cameroon in August 2016. Data collection was done by interview with a questionnaire and by observation regarding the availability of resources and materials for surveillance and case management, access to water, hygiene, and sanitation. Data analysis was descriptive with STATA 11.

PRINCIPAL FINDINGS

A total of 134 health facilities were evaluated, most of which (108/134[81%]) were urban facilities. The preparedness regarding surveillance was limited with 13 (50%) health facilities in the Far North and 22(20%) in the Littoral having cholera case definition guide. ORS for Case management was present in 8(31%) health facilities in the Far North and in 94(87%) facilities in the littoral. Less than half of the health facilities had a hand washing protocol and 7(5.1%) did not have any source of drinking water or relied on unimproved sources like lake. A total of 4(3.0%) health facilities, all in the Far North region, did not have a toilet.

CONCLUSIONS

The level of preparedness of health facilities in Cameroon for cholera outbreak response presents a lot of weaknesses. These are present in terms of lack of basic surveillance and case management materials and resources, low access to WaSH. If not addressed now, these facilities might not be able to play their role in case there is an outbreak and might even turn to be transmission milieus.

Characterization of the Spatial and Temporal Distribution of Nipah Virus Spillover Events in Bangladesh, 2007-2013

Nipah virus is a zoonotic virus harbored by bats and lethal to humans. Bat-to-human spillovers occur every winter in Bangladesh. However, there is significant heterogeneity in the number of spillovers detected by district and year that remains unexplained. We analyzed data from all 57 spillovers during 2007-2013 and found that temperature differences explained 36% of the year-to-year variation in the total number of spillovers each winter and that distance to surveillance hospitals explained 45% of spatial heterogeneity. Interventions to prevent human infections may be most important during colder winters. Further work is needed to understand how dynamics of bat infections explains spillover risk.

Changes in inequality of childhood morbidity in Bangladesh 1993-2014: A decomposition analysis

INTRODUCTION

Child health remains an important public health concern at the global level, with preventable diseases such as diarrheal disease, acute respiratory infection (ARI) and fever posing a large public health burden in low- and middle-income countries including Bangladesh. Improvements in socio-economic conditions have tended to benefit advantaged groups in societies, which has resulted in widespread inequalities in health outcomes. This study examined how socioeconomic inequality is associated with childhood morbidity in Bangladesh, and identified the factors affecting three illnesses: diarrhea, ARI and fever.

MATERIALS AND METHODS

A total of 43,860 sample observations from the Bangladesh Demographic and Health Survey, spanning a 22-year period (1993-2014), were analysed. Concentration curve and concentration index methods were used to evaluate changes in the degree of household wealth-related inequalities and related trends in childhood morbidity. Regression-based decomposition analyses were used to attribute the inequality disparities to individual determinants for the three selected causes of childhood morbidity.

RESULTS

The overall magnitude of inequality in relation to childhood morbidity has been declining slowly over the 22-year period. The magnitude of socio-economic inequality as a cause of childhood morbidity varied during the period. Decomposition analyses attributed the inequalities to poor maternal education attainment, inadequate pre-delivery care, adverse chronic undernutrition status and low immunisation coverage.

CONCLUSIONS

High rates of childhood morbidity were observed, although these have declined over time. Socio-economic inequality is strongly associated with childhood morbidity. Socio-economically disadvantaged communities need to be assisted and interventions should emphasise improvements of, and easier access to, health care services. These will be key to improving the health status of children in Bangladesh and should reduce economic inequality through improved health over time.

Estimating undetected Ebola spillovers

The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events and outbreaks do not generate data. Using three independent datasets available on the distributions of secondary infections during EVD outbreaks across West Africa, in a single district (Western Area) of Sierra Leone, and in the city of Conakry, Guinea, we simulated realistic outbreak size distributions and compared them to reported outbreak sizes. These three empirical distributions lead to estimates for the proportion of detected spillover events and small outbreaks of 26% (range 8-40%, based on the full outbreak data), 48% (range 39-62%, based on the Sierra Leone data), and 17% (range 11-24%, based on the Guinea data). We conclude that at least half of all spillover events have failed to be reported since EVD was first recognized. We also estimate the probability of detecting outbreaks of different sizes, which is likely less than 10% for single-case spillover events. Comparing models of the observation process also suggests the probability of detecting an outbreak is not simply the cumulative probability of independently detecting any one individual. Rather, we find that any individual's probability of detection is highly dependent upon the size of the cluster of cases. These findings highlight the importance of primary health care and local case management to detect and contain undetected early stage outbreaks at source.

Factors Influencing Community Event-based Surveillance: Lessons Learned from Pilot Implementation in Vietnam

Community event-based surveillance aims to enhance the early detection of emerging public health threats and thus build health security. The Ministry of Health of Vietnam launched a community event-based surveillance pilot program in 6 provinces to improve the early warning functions of the existing surveillance system. An evaluation of the pilot program took place in 2017 and 2018. Data from this evaluation were analyzed to determine which factors were associated with increased detection and reporting. Results show that a number of small, local events were detected and reported through community event-based surveillance, supporting the notion that it would also facilitate the rapid detection and reporting of potentially larger events or outbreaks. The study showed the value of supportive supervision and monitoring to sustain community health worker reporting and the importance of conducting evaluations for community event-based surveillance programs to identify barriers to effective implementation.

Incidence of Acute Diarrhea-Associated Death among Children < 5 Years of Age in Bangladesh, 2010-12

Although acute diarrheal deaths have declined globally among children < 5 years, it may still contribute to childhood mortality as an underlying or contributing cause. The aim of this project was to estimate the incidence of acute diarrhea-associated deaths, regardless of primary cause, among children < 5 years in Bangladesh during 2010-12. We conducted a survey in 20 unions (administrative units) within the catchment areas of 10 tertiary hospitals in Bangladesh. Through social networks, our field team identified households where children < 5 years were reported to have died during 2010-12. Trained data collectors interviewed caregivers of the deceased children and recorded illness symptoms, health care seeking, and other information using an abbreviated international verbal autopsy questionnaire. We classified the deceased based upon the presence of diarrhea before death. We identified 880 deaths, of which 36 (4%) died after the development of acute diarrhea, 17 (2%) had diarrhea-only in the illness preceding death, and 19 (53%) had cough or difficulty breathing in addition to diarrhea. The estimated annual incidence of all-cause mortality in the unions < 13.6 km of the tertiary hospitals was 26 (95% confidence interval [CI] 16-37) per 1,000 live births compared with the mortality rate of 37 (95% CI 26-49) per 1,000 live births in the unions located ≥ 13.6 km. Diarrhea contributes to childhood death at a higher proportion than when considering it only as the sole underlying cause of death. These data support the use of interventions aimed at preventing acute diarrhea, especially available vaccinations for common etiologies, such as rotavirus.