Data quality and timeliness of outbreak reporting system among countries in Greater Mekong subregion: Challenges for international data sharing

Rapid response teams in the Eastern Mediterranean Region: Results from the baseline survey of country-level capacities, operations and outbreak response capabilities

The aim of this study is to assess WHO/Eastern Mediterranean region (WHO/EMR) countries capacities, operations and outbreak response capabilities. Cross-sectional study was conducted targeting 22 WHO/EMR countries from May to June 2021. The survey covers 8 domains related to 15 milstones and key performance indicators (KPIs) for RRT. Responses were received from 14 countries. RRTs are adequately organised in 9 countries (64.3%). The mean retention rate of RRT members was 85.5% ± 22.6. Eight countries (57.1%) reported having standard operating procedures, but only three countries (21.4%) reported an established mechanism of operational fund allocation. In the last 6 months, 10,462 (81.9%) alerts were verified during the first 24 h. Outbreak response was completed by the submission of final RRT response reports in 75% of analysed outbreaks. Risk Communication and Community Engagement (RCCE) activities were part of the interventional response in 59.5% of recent outbreaks. Four countries (28.6%) reported an adequate system to assess RRTs operations. The baseline data highlights four areas to focus on: developing and maintaining the multidisciplinary nature of RRTs through training, adequate financing and timely release of funds, capacity and system building for implementing interventions, for instance, RCCE, and establishing national monitoring and evaluation systems for outbreak response.

Implementation of the 7-1-7 target for detection, notification, and response to public health threats in five countries: a retrospective, observational study

BACKGROUND

Suboptimal detection and response to recent outbreaks, including COVID-19 and mpox (formerly known as monkeypox), have shown that the world is insufficiently prepared for public health threats. Routine monitoring of detection and response performance of health emergency systems through timeliness metrics has been proposed to evaluate and improve outbreak preparedness and contain health threats early. We implemented 7-1-7 to measure the timeliness of detection (target of ≤7 days from emergence), notification (target of ≤1 day from detection), and completion of seven early response actions (target of ≤7 days from notification), and we identified bottlenecks to and enablers of system performance.

METHODS

In this retrospective, observational study, we conducted reviews of public health events in Brazil, Ethiopia, Liberia, Nigeria, and Uganda with staff from ministries of health and national public health institutes. For selected public health events occurring from Jan 1, 2018, to Dec 31, 2022, we calculated timeliness intervals for detection, notification, and early response actions, and synthesised identified bottlenecks and enablers. We mapped bottlenecks and enablers to Joint External Evaluation (second edition) indicators.

FINDINGS

Of 41 public health events assessed, 22 (54%) met a target of 7 days to detect (median 6 days [range 0-157]), 29 (71%) met a target of 1 day to notify (0 days [0-24]), and 20 (49%) met a target of 7 days to complete all early response actions (8 days [0-72]). 11 (27%) events met the complete 7-1-7 target, with variation among event types. 25 (61%) of 41 bottlenecks to and 27 (51%) of 53 enablers of detection were at the health facility level, with delays to notification (14 [44%] of 32 bottlenecks) and response (22 [39%] of 56 bottlenecks) most often at an intermediate public health (ie, municipal, district, county, state, or province) level. Rapid resource mobilisation for responses (six [9%] of 65 enablers) from the national level enabled faster responses.

INTERPRETATION

The 7-1-7 target is feasible to measure and to achieve, and assessment with this framework can identify areas for performance improvement and help prioritise national planning. Increased investments must be made at the health facility and intermediate public health levels for improved systems to detect, notify, and rapidly respond to emerging public health threats.

FUNDING

Bill & Melinda Gates Foundation.

Rabies in Southeast Asia: a systematic review of its incidence, risk factors and mortality

OBJECTIVE

Rabies is a neglected zoonotic disease that can infect all mammals, including humans. We aimed to summarise the current knowledge of the incidence, risk factors and mortality of rabies in Southeast Asia.

DESIGN

Systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020.

DATA SOURCES

Scopus, Web of Science and PubMed were searched from 1 January 2012 to 21 February 2023.

ELIGIBILITY CRITERIA

Original English language articles published between 2012 and 2023 were included.

DATA EXTRACTION AND SYNTHESIS

Nine independent reviewers extracted data and assessed the risk of bias. The quality appraisal of included articles was carried out using the Mixed Methods Appraisal Tool.

RESULTS

A total of eight articles were included in this analysis. In Vietnam, the incidence of rabies ranged from 1.7 to 117.2 per 100 000 population. The cumulative incidence in Sarawak was estimated at 1.7 per 100 000 population. In Indonesia, 104 human rabies cases were reported from 2008 to 2010, while in Thailand, a total of 46 rabies cases were reported in Thailand from 2010 to 2015. In the Philippines, the incidence of rabies ranged from 0.1 to 0.3 per 100 000 population. An increased risk of rabies virus infection was associated with a high population density, illiteracy, seasonal patterns and dog butchers. The case fatality rate was 100%.

CONCLUSION

This study included research from Southeast Asia, which may not represent rabies infection in other regions or continents. In addition, the role of publication bias should be acknowledged as grey literature was not included. The occurrence of rabies in Southeast Asia is due to the high number of unvaccinated stray and pet dogs, working hazards (dog butchers in Vietnam), the unavailability of the rabies vaccine in rural regions and misinformation about the significance of seeking treatment after dog bites.

PROSPERO REGISTRATION NUMBER

CRD42022311654.

Phylogenetic Analysis of Transmission Dynamics of Dengue in Large and Small Population Centers, Northern Ecuador

Although dengue is typically considered an urban disease, rural communities are also at high risk. To clarify dynamics of dengue virus (DENV) transmission in settings with characteristics generally considered rural (e.g., lower population density, remoteness), we conducted a phylogenetic analysis in 6 communities in northwestern Ecuador. DENV RNA was detected by PCR in 121/488 serum samples collected from febrile case-patients during 2019-2021. Phylogenetic analysis of 27 samples from Ecuador and other countries in South America confirmed that DENV-1 circulated during May 2019-March 2020 and DENV-2 circulated during December 2020-July 2021. Combining locality and isolation dates, we found strong evidence that DENV entered Ecuador through the northern province of Esmeraldas. Phylogenetic patterns suggest that, within this province, communities with larger populations and commercial centers were more often the source of DENV but that smaller, remote communities also play a role in regional transmission dynamics.

A framework for measuring timeliness in the outbreak response path: lessons learned from the Middle East respiratory syndrome (MERS) epidemic, September 2012 to January 2019

BackgroundEpidemics are a constant threat in the 21st century, particularly disease outbreaks following spillover of an animal virus to humans. Timeliness, a key metric in epidemic response, can be examined to identify critical steps and delays in public health action.AimTo examine timeliness, we analysed the response to the Middle East respiratory syndrome (MERS) epidemic, with a focus on the international and One Health response efforts.MethodsWe performed a historical review of the MERS epidemic between September 2012 and January 2019 in three steps: (i) the construction of a timeline identifying critical events in the global response, (ii) the performance of a critical path analysis to define outbreak milestones and (iii) a time gap analysis to measure timeliness in the execution of these milestones.ResultsWe proposed 14 MERS-specific milestones at different phases of the epidemic, assessing timeliness of the public health response as well as at the animal-human interface, where we identified the most significant delays.ConclusionsWhen comparing timeliness across three coronavirus epidemics, i.e. MERS (2012), SARS (2002) and COVID-19 (2019), we identified clear improvements over time for certain milestones including laboratory confirmation and diagnostics development, while this was not as apparent for others, as the identification of zoonotic hosts. To more efficiently respond to emerging threats, the global health community should widely assess and tackle specific delays in implementing response interventions by addressing challenges in the sharing of information, data and resources, as well as efficiency, quality, transparency and reliability of reporting events.

Evaluating Completeness of Foodborne Outbreak Reporting in the United States, 1998-2019

Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling. We described the completeness of 103 variables for 22,792 outbreaks publicly reported by the United States Centers for Disease Control and Prevention’s (US CDC’s) electronic Foodborne Outbreak Reporting System (eFORS) and National Outbreak Reporting System (NORS). We compared monthly trends of completeness during eFORS (1998−2008) and NORS (2009−2019) reporting periods using segmented time series analyses adjusted for seasonality. We quantified the overall, annual, and monthly completeness as the percentage of outbreaks with blank records per our study period, calendar year, and study month, respectively. We found that outbreaks of unknown genus (n = 7401), Norovirus (n = 6414), Salmonella (n = 2872), Clostridium (n = 944), and multiple genera (n = 779) accounted for 80.77% of all outbreaks. However, crude completeness ranged from 46.06% to 60.19% across the 103 variables assessed. Variables with the lowest crude completeness (ranging 3.32−6.98%) included pathogen, specimen etiological testing, and secondary transmission traceback information. Variables with low (<35%) average monthly completeness during eFORS increased by 0.33−0.40%/month after transitioning to NORS, most likely due to the expansion of surveillance capacity and coverage within the new reporting system. Examining completeness metrics in outbreak surveillance systems provides essential information on the availability of data for public reuse. These metadata offer important insights for public health statisticians and modelers to precisely monitor and track the geographic spread, event duration, and illness intensity of foodborne outbreaks.

Data collection for outbreak investigations: process for defining a minimal data set using a Delphi approach

Background

Timely but accurate data collection is needed during health emergencies to inform public health responses. Often, an abundance of data is collected but not used. When outbreaks and other health events occur in remote and complex settings, operatives on the ground are often required to cover multiple tasks whilst working with limited resources. Tools that facilitate the collection of essential data during the early investigations of a potential public health event can support effective public health decision-making. We proposed to define the minimum set of quantitative information to collect whilst using electronic device or not. Here we present the process used to select the minimum information required to describe an outbreak of any cause during its initial stages and occurring in remote settings.

Methods

A working group of epidemiologists took part in two rounds of a Delphi process to categorise the variables to be included in an initial outbreak investigation form. This took place between January–June 2019 using an online survey.

Results

At a threshold of 75 %, consensus was reached for nineteen (23.2%) variables which were all classified as ‘essential’. This increased to twenty-six (31.7%) variables when the threshold was reduced to 60% with all but one variable classified as ‘essential’. Twenty-five of these variables were included in the ‘Time zero initial case investigation’ ‘(T0)’ form which was shared with the members of the Rapid Response Team Knowledge Network for field testing and feedback. The form has been readily available online by WHO since September 2019.

Conclusion

This is the first known Delphi process used to determine the minimum variables needed for an outbreak investigation. The subsequent development of the T0 form should help to improve the efficiency and standardisation of data collection during emergencies and ultimately the quality of the data collected during field investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12206-5.

Equitable data sharing in epidemics and pandemics

BACKGROUND

Rapid data sharing can maximize the utility of data. In epidemics and pandemics like Zika, Ebola, and COVID-19, the case for such practices seems especially urgent and warranted. Yet rapidly sharing data widely has previously generated significant concerns related to equity. The continued lack of understanding and guidance on equitable data sharing raises the following questions: Should data sharing in epidemics and pandemics primarily advance utility, or should it advance equity as well? If so, what norms comprise equitable data sharing in epidemics and pandemics? Do these norms address the equity-related concerns raised by researchers, data providers, and other stakeholders? What tensions must be balanced between equity and other values?

METHODS

To explore these questions, we undertook a systematic scoping review of the literature on data sharing in epidemics and pandemics and thematically analyzed identified literature for its discussion of ethical values, norms, concerns, and tensions, with a particular (but not exclusive) emphasis on equity. We wanted to both understand how equity in data sharing is being conceptualized and draw out other important values and norms for data sharing in epidemics and pandemics.

RESULTS

We found that values of utility, equity, solidarity, and reciprocity were described, and we report their associated norms, including researcher recognition; rapid, real-time sharing; capacity development; and fair benefits to data generators, data providers, and source countries. The value of utility and its associated norms were discussed substantially more than others. Tensions between utility norms (e.g., rapid, real-time sharing) and equity norms (e.g., researcher recognition, equitable access) were raised.

CONCLUSIONS

This study found support for equity being advanced by data sharing in epidemics and pandemics. However, norms for equitable data sharing in epidemics and pandemics require further development, particularly in relation to power sharing and participatory approaches prioritizing inclusion. Addressing structural inequities in the wider global health landscape is also needed to achieve equitable data sharing in epidemics and pandemics.

The utilisation of tools to facilitate cross-border communication during international food safety events, 1995-2020: a realist synthesis

Efficient communication and coordination are needed between countries to prevent, detect and respond to international food safety events. While communication tools, networks and systems exist, current evidence suggests that they are only useful within particular contexts and several only target specific geographic areas. There is a need to unpack and explore the mechanisms of how and in what context such communication tools and their components are effective at facilitating international communication and coordination to keep food safe and mitigate the burden of foodborne disease around the world.

A realist synthesis was undertaken to understand how and why certain processes and structures of communication tools, used during international food safety events, influence their utility and effectiveness according to different contextual factors. The focus of this review was explanatory and aimed to develop and refine theory regarding how contextual factors trigger specific processes and mechanisms to produce outcomes. Using the realist context–mechanism–outcome configuration of theory development, a range of sources was used to develop an initial programme theory, including the authors’ experience, a scoping review of published papers and grey literature and input from an expert reference committee. Literature was then systematically located and synthesised from several databases with input from the expert reference committee to refine the programme theory.

The programme theory developed indicates that when a country has interests in food import or export, has the technical infrastructure to detect and respond to food safety events, and is governed in accordance with regional and/or global laws and regulations relating to food control and global health security, then specific mechanisms will facilitate various outcomes. Mechanisms include trust, experience, support, awareness, understanding, a sense of community, standardisation and intersectoral collaboration. The outcomes include using communication tools to relay information abroad and the prevention of foodborne diseases, among others.

Components of such communication tools may be adapted according to different contextual factors to promote, support and improve their use. Improving international coordination and communication during international food safety events is in the interest of global health security and can mitigate the global burden of foodborne disease.

Diagnostic accuracy of the WHO clinical definitions for dengue and implications for surveillance: A systematic review and meta-analysis

Background

Dengue is the world’s most common mosquito-borne virus but remains diagnostically challenging due to its nonspecific presentation. Access to laboratory confirmation is limited and thus most reported figures are based on clinical diagnosis alone, the accuracy of which is uncertain. This systematic review assesses the diagnostic accuracy of the traditional (1997) and revised (2009) WHO clinical case definitions for dengue fever, the basis for most national guidelines.

Methodology/Principal findings

PubMed, EMBASE, Scopus, OpenGrey, and the annual Dengue Bulletin were searched for studies assessing the diagnostic accuracy of the unmodified clinical criteria. Two reviewers (NR/SL) independently assessed eligibility, extracted data, and evaluated risk of bias using a modified QUADAS-2. Additional records were found by citation network analysis. A meta-analysis was done using a bivariate mixed-effects regression model. Studies that modified criteria were analysed separately. This systematic review protocol was registered on PROSPERO (CRD42020165998). We identified 11 and 12 datasets assessing the 1997 and 2009 definition, respectively, and 6 using modified criteria. Sensitivity was 93% (95% CI: 77–98) and 93% (95% CI: 86–96) for the 1997 and 2009 definitions, respectively. Specificity was 29% (95% CI: 8–65) and 31% (95% CI: 18–48) for the 1997 and 2009 definitions, respectively. Diagnostic performance suffered at the extremes of age. No modification significantly improved accuracy.

Conclusions/Significance

Diagnostic accuracy of clinical criteria is poor, with significant implications for surveillance and public health responses for dengue control. As the basis for most reported figures, this has relevance to policymakers planning resource allocation and researchers modelling transmission, particularly during COVID-19.

Dengue is the most common mosquito-borne disease worldwide, with half the world’s population living in at-risk areas, yet it remains difficult to diagnose. Existing laboratory tests have highly variable performance, and access to them remains limited in most dengue-endemic regions. Thus, most dengue cases are diagnosed on clinical criteria alone. While national guidelines vary, most are based on the WHO case definitions, produced in 1997 and revised in 2009. Here, we assess the diagnostic accuracy of both definitions and find that they have good sensitivity but poor specificity, particularly problematic given the co-circulation of multiple febrile illnesses in these regions. This makes it difficult for policymakers and researchers to model transmission, assess the introduction of new pathogens to a region, and correctly prioritise control measures and vaccination programmes in a region-specific manner. This is exacerbated by the ongoing COVID-19 pandemic, given rising cases of both diseases and the stark difference in necessary control measures. As such, improvements in dengue diagnostic and reporting practice are increasingly urgent. This could be achieved by incorporating symptom absence into clinical criteria, weighting symptoms depending on strength of association with dengue or timing within disease course, or using clinical criteria to allocate limited testing resources in borderline cases.

Using Timeliness Metrics to Track Progress and Identify Gaps in Disease Surveillance

Timely outbreak detection and response can translate into illnesses averted and lives saved. As such, timeliness is an important criterion for evaluating performance of infectious disease surveillance systems. Through the use of clearly defined outbreak milestones, timeliness metrics can capture the speed of outbreak detection, verification, response, and other key actions across the timeline of an outbreak and evaluate progress over time. In this article, we describe a series of country-level pilot studies designed to assess the feasibility and utility of tracking timeliness metrics and highlight key findings. We then discuss subsequent efforts to develop a timeliness metrics measurement framework through expert consultation and provide recommendations for implementation. National surveillance programs, international agencies, and donor organizations can use timeliness metrics to identify gaps in surveillance performance and track progress toward improved global health security.

Common and Unique Barriers to the Exchange of Administrative Healthcare Data in Environmental Public Health Tracking Program

CDC’s National Environmental Public Health Tracking Program (Tracking Program) receives administrative data annually from 25–30 states to track potential environmental exposures and to make data available for public access. In 2019, the CDC Tracking Program conducted a cross-sectional survey among principal investigators or program managers of the 26 funded programs to improve access to timely, accurate, and local data. All 26 funding recipients reported having access to hospital inpatient data, and most states (69.2%) regularly update data user agreements to receive the data. Among the respondents, 15 receive record-level data with protected health information (PHI) and seven receive record-level data without PHI. Regarding geospatial resolution, approximately 50.0% of recipients have access to the street address or census tract information, 34.6% have access to ZIP code, and 11.5% have other sub-county geographies (e.g., town). Only three states receive administrative data for their residents from all border states. The survey results will help the Tracking Program to identify knowledge gaps and perceived barriers to the use and accessibility of administrative data for the CDC Tracking Program. The information collected will inform the development of resources that can provide solutions for more efficient and timely data exchange.

An Assessment of Timeliness and Quality of Communicable Disease Surveillance System in the Kurdistan Region of Iraq

Background

The quality of the surveillance system can be defined by attributes such as completeness, timeliness, usefulness, simplicity, flexibility, acceptability, and reliability. This study aims to assess these quality features of the communicable disease surveillance system (CDSS) in the Kurdistan Region of Iraq.

Methods

This study was conducted using a retrospective review of records and documents, and the interviews with the surveillance staff (n = 82) of the Kurdistan governorates during 2018, 2019, and 2020. The World Health Organization (WHO) guideline 2006 indicators were used for evaluation and monitoring the quality of the communicable disease surveillance system. The data analyzed and showed as frequencies and percentages using Statistical Package for the Social Sciences (SPSS) version 26 software.

Results

The reporting timeliness declined from 98% in 2019 to 69% in 2020. At the same time, there was an improvement in completeness of reporting from 83% in 2018 to 99% in 2020. The total scores of other surveillance quality attributes, simplicity, usefulness, flexibility, acceptability, and reliability, were 75%, 72%, 67%, 72%, and 69%, respectively.

Conclusion

Current findings demonstrate that the CDSS is still facing significant challenges in timeliness simplicity, usefulness, flexibility, acceptability, and reliability. Further studies to assess the system’s quality, particularly the system’s timeliness of outbreak response, sensitivity, and specificity, are recommended.

Data Sharing in Southeast Asia During the First Wave of the COVID-19 Pandemic

Background: When a new pathogen emerges, consistent case reporting is critical for public health surveillance. Tracking cases geographically and over time is key for understanding the spread of an infectious disease and effectively designing interventions to contain and mitigate an epidemic. In this paper we describe the reporting systems on COVID-19 in Southeast Asia during the first wave in 2020, and highlight the impact of specific reporting methods. Methods: We reviewed key epidemiological variables from various sources including a regionally comprehensive dataset, national trackers, dashboards, and case bulletins for 11 countries during the first wave of the epidemic in Southeast Asia. We recorded timelines of shifts in epidemiological reporting systems and described the differences in how epidemiological data are reported across countries and timepoints. Results: Our findings suggest that countries in Southeast Asia generally reported precise and detailed epidemiological data during the first wave of the pandemic. Changes in reporting rarely occurred for demographic data, while reporting shifts for geographic and temporal data were frequent. Most countries provided COVID-19 individual-level data daily using HTML and PDF, necessitating scraping and extraction before data could be used in analyses. Conclusion: Our study highlights the importance of more nuanced analyses of COVID-19 epidemiological data within and across countries because of the frequent shifts in reporting. As governments continue to respond to impacts on health and the economy, data sharing also needs to be prioritised given its foundational role in policymaking, and in the implementation and evaluation of interventions.

Early detection of cholera epidemics to support control in fragile states: estimation of delays and potential epidemic sizes

BACKGROUND

Cholera epidemics continue to challenge disease control, particularly in fragile and conflict-affected states. Rapid detection and response to small cholera clusters is key for efficient control before an epidemic propagates. To understand the capacity for early response in fragile states, we investigated delays in outbreak detection, investigation, response, and laboratory confirmation, and we estimated epidemic sizes. We assessed predictors of delays, and annual changes in response time.

METHODS

We compiled a list of cholera outbreaks in fragile and conflict-affected states from 2008 to 2019. We searched for peer-reviewed articles and epidemiological reports. We evaluated delays from the dates of symptom onset of the primary case, and the earliest dates of outbreak detection, investigation, response, and confirmation. Information on how the outbreak was alerted was summarized. A branching process model was used to estimate epidemic size at each delay. Regression models were used to investigate the association between predictors and delays to response.

RESULTS

Seventy-six outbreaks from 34 countries were included. Median delays spanned 1-2 weeks: from symptom onset of the primary case to presentation at the health facility (5 days, IQR 5-5), detection (5 days, IQR 5-6), investigation (7 days, IQR 5.8-13.3), response (10 days, IQR 7-18), and confirmation (11 days, IQR 7-16). In the model simulation, the median delay to response (10 days) with 3 seed cases led to a median epidemic size of 12 cases (upper range, 47) and 8% of outbreaks ≥ 20 cases (increasing to 32% with a 30-day delay to response). Increased outbreak size at detection (10 seed cases) and a 10-day median delay to response resulted in an epidemic size of 34 cases (upper range 67 cases) and < 1% of outbreaks < 20 cases. We estimated an annual global decrease in delay to response of 5.2% (95% CI 0.5-9.6, p = 0.03). Outbreaks signaled by immediate alerts were associated with a reduction in delay to response of 39.3% (95% CI 5.7-61.0, p = 0.03).

CONCLUSIONS

From 2008 to 2019, median delays from symptom onset of the primary case to case presentation and to response were 5 days and 10 days, respectively. Our model simulations suggest that depending on the outbreak size (3 versus 10 seed cases), in 8 to 99% of scenarios, a 10-day delay to response would result in large clusters that would be difficult to contain. Improving the delay to response involves rethinking the integration at local levels of event-based detection, rapid diagnostic testing for cluster validation, and integrated alert, investigation, and response.

Involvement of the open-source community in combating the worldwide COVID-19 pandemic: a review

The ongoing COVID-19 pandemic is unprecedented in the modern age both due to its scale and its disruption to daily life throughout the world. Widespread social isolation and restrictions in the age of modern communicative technology, coupled with some early successes for makers, have united the open-source community towards a common goal in a way not previously seen. Local hospitals and care facilities are turning to makers to print essential consumable parts, such as simple visors, while in the hardest hit areas, critical pieces of medical technology are being fabricated. While important and effective innovations are appearing almost daily, there are also some worrying trends towards hobbyists attempting manufacture of complex medical devices with little understanding of the clinical or scientific rationale behind their design. The nature of the open-source community, an area of intensive innovation, fluidity, and experimentation, jars with the exacting standards of medical device regulation. Here, we review the involvement of rapid prototyping and the open-source community in the key areas of personal protective equipment (PPE), diagnostics, critical care technology, and information acquisition and sharing, highlighting where makers and hackers have clashed with medical device regulations, and areas where the system has worked well to facilitate change.

On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management

As the Coronavirus (COVID-19) expands its impact from China, expanding its catchment into surrounding regions and other countries, increased national and international measures are being taken to contain the outbreak. The placing of entire cities in ‘lockdown’ directly affects urban economies on a multi-lateral level, including from social and economic standpoints. This is being emphasised as the outbreak gains ground in other countries, leading towards a global health emergency, and as global collaboration is sought in numerous quarters. However, while effective protocols in regard to the sharing of health data is emphasised, urban data, on the other hand, specifically relating to urban health and safe city concepts, is still viewed from a nationalist perspective as solely benefiting a nation’s economy and its economic and political influence. This perspective paper, written one month after detection and during the outbreak, surveys the virus outbreak from an urban standpoint and advances how smart city networks should work towards enhancing standardization protocols for increased data sharing in the event of outbreaks or disasters, leading to better global understanding and management of the same.

Improving Cross-Border Preparedness and Response: Lessons Learned from 3 Lassa Fever Outbreaks Across Benin, Nigeria, and Togo, 2017-2019

Long-standing cultural, economic, and political relationships among Benin, Nigeria, and Togo contribute to the complexity of their cross-border connectivity. The associated human movement increases the risk of international spread of communicable disease. The Benin and Togo ministries of health and the Nigeria Centre for Disease Control, in collaboration with the Abidjan Lagos Corridor Organization (a 5-country intergovernmental organization) and the US Centers for Disease Control and Prevention, sought to minimize the risk of cross-border outbreaks by defining and implementing procedures for binational and multinational public health collaboration. Through 2 multinational meetings, regular district-level binational meetings, and fieldwork to characterize population movement and connectivity patterns, the countries improved cross-border public health coordination. Across 3 sequential cross-border Lassa fever outbreaks identified in Benin or Togo between February 2017 and March 2019, the 3 countries improved their collection and sharing of patients' cross-border travel histories, shortened the time between case identification and cross-border information sharing, and streamlined multinational coordination during response efforts. Notably, they refined collaborative efforts using lessons learned from the January to March 2018 Benin outbreak, which had a 100% case fatality rate among the 5 laboratory-confirmed cases, 3 of whom migrated from Nigeria across porous borders when ill. Aligning countries' expectations for sharing public health information would assist in reducing the international spread of communicable diseases by facilitating coordinated preparedness and responses strategies. Additionally, these binational and multinational strategies could be made more effective by tailoring them to the unique cultural connections and population movement patterns in the region.

Whole Genome Sequencing for Surveillance of Diphtheria in Low Incidence Settings

Corynebacterium diphtheriae (C. diphtheriae) is a relatively rare pathogen in most Western countries. While toxin producing strains can cause pharyngeal diphtheria with potentially fatal outcomes, the more common presentation is wound infections. The diphtheria toxin is encoded on a prophage and can also be carried by Corynebacterium ulcerans and Corynebacterium pseudotuberculosis. Currently, across Europe, infections are mainly diagnosed in travelers and refugees from regions where diphtheria is more endemic, patients from urban areas with poor hygiene, and intravenous drug users. About half of the cases are non-toxin producing isolates. Rapid identification of the bacterial pathogen and toxin production is a critical element of patient and outbreak management. Beside the immediate clinical management of the patient, public health agencies should be informed of toxigenic C. diphtheriae diagnoses as soon as possible. The collection of case-related epidemiological data from the patient is often challenging due to language barriers and social circumstances. However, information on patient contacts, vaccine status and travel/refugee route, where appropriate, is critical, and should be documented. In addition, isolates should be characterized using high resolution typing, in order to identify transmissions and outbreaks. In recent years, whole genome sequencing (WGS) has become the gold standard of high-resolution typing methods, allowing detailed investigations of pathogen transmissions. De-centralized sequencing strategies with redundancy in sequencing capacities, followed by data exchange may be a valuable future option, especially since WGS becomes more available and portable. In this context, the sharing of sequence data, using public available platforms, is essential. A close interaction between microbiology laboratories, treating physicians, refugee centers, social workers, and public health officials is a key element in successful management of suspected outbreaks. Analyzing bacterial isolates at reference centers may further help to provide more specialized microbiological techniques and to standardize information, but this is also more time consuming during an outbreak. Centralized communication strategies between public health agencies and laboratories helps considerably in establishing and coordinating effective surveillance and infection control. We review the current literature on high-resolution typing of C. diphtheriae and share our own experience with the coordination of a Swiss-German outbreak.

Use of systematic epidemiological methods in outbreak investigations from India, 2008-2016: A systematic review

Background

In the absence of a comprehensive review, we conducted a systematic review on the use of systematic approach in outbreak investigation using reports from India.

Objectives

The primary objective was to estimate the proportion of outbreak reports from India during 2008–16, that reported the steps in outbreak investigation. The secondary objectives were to (1) describe the outbreak reports by selected characteristics (source, investigating agency, disease, time, place and person) (2) estimate the proportion of outbreaks that conducted analytical and additional studies.

Methods

We searched eight electronic databases and grey literature for outbreak investigation reports among humans at community settings from India during 2008–2016. We developed a check-list based on the 10-steps approach used by Field Epidemiology Training Programme (FETP) of ICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India. This checklist was used to independently screen and extract data on general characteristics of the outbreak investigation reports and the steps completed. We adopted The Joanna Briggs Institute (JBI) check list for prevalence studies to examine the credibility and consistency. The protocol was registered at Prospero (CRD42017065038). We calculated proportion of reports that followed the steps in their investigation and descriptive statistics on selected characteristics.

Results

Of 10,657 articles screened, 136 articles were included for the review. Completion of the ten steps in the outbreak investigations was seen in 16% of reports. The highest level of completion was for drawing conclusion in outbreak investigation (98%) and the lowest completion (29%) was for developing a case definition by time, place and person followed by conducting an analytic study (24%).

Conclusions

Outbreak reports from India either lacked application of systematic steps for investigation or failed to report the actual procedures followed. We recommend improving systematic investigation of outbreaks through training and supervision of outbreak response teams and encouraging publications.

•

Systematic review of outbreak investigation reports from India (2008–16) for application of systematic approach documented poor application of use of methods used or reporting of recommended steps.

•

Defining of a case by time, place and person and conducting an analytic study were the least reported steps.

•

There is a need to strengthen the quality and transparency of outbreak investigations while reporting.