Beyond traditional surveillance: applying syndromic surveillance to developing settings--opportunities and challenges

Prevalence of and risk factors for infectious disease syndromic symptoms among pilgrimage to Arba'een mass gathering religious in 2023

Background

There is a growing participation of Shia Muslims, in the Arba'een pilgrimage every year. It is imperative to conduct a comprehensive study on the transmission of diseases among Arba'een pilgrims in order to identify and promptly respond to potential epidemics effectively. We aimed to assess the syndromic symptoms associated with infectious diseases and the prevalence of mask usage among patients visiting outpatient clinics during the Arba'een pilgrimage in Ira, in 2023.

Methods

In this descriptive-analytical study, 300 outpatients who sought medical care at outpatient clinics during the Arba'een pilgrimage were randomly selected. The study data and infectious disease syndromic symptoms were assessed using trained healthcare professionals. A multiple logistic regression analysis was carried out to estimate the crude and Adjusted odds ratios (AORs) of symptoms and risk factors associated with respiratory syndrome and flu-like symptoms with 95 % confidence intervals.

Results

The mean age of the participants was 39 years and 61 % of those were male. Out of 72 (24 %) of mask users, 41.6 % had changed masks in less than 8 h. The most common syndromic symptoms was Flu-like illness (53 %). In the final analysis, not wearing a mask AOR = 1.40 (1.1-9.8) and smoking AOR = 3.25 (1.1-9.5) both elevated the risk of the flu-like syndrome and severe respiratory disease symptoms.

Conclusions

Pilgrims are especially vulnerable to the flu and other respiratory illnesses. Therefore, performing a differential diagnosis in these people, including flu and COVID-19, is essential to prevent an outbreak during the Arba'een pilgrimage.

Utility of syndromic surveillance for the surveillance of healthcare-associated infections in resource-limited settings: a narrative review

Globally, Healthcare-associated infections (HCAIs) pose a significant threat to patient safety and healthcare systems. In low- and middle-income countries (LMICs), the lack of adequate resources to manage HCAIs, as well as the weak healthcare system, further exacerbate the burden of these infections. Traditional surveillance methods that rely on laboratory tests are cost-intensive and impractical in these settings, leading to ineffective monitoring and delayed management of HCAIs. The rates of HCAIs in resource-limited settings have not been well established for most LMICs, despite their negative consequences. This is partly due to costs associated with surveillance systems. Syndromic surveillance, a part of active surveillance, focuses on clinical observations and symptoms rather than laboratory confirmation for HCAI detection. Its cost-effectiveness and efficiency make it a beneficial approach for monitoring HCAIs in LMICs. It provides for early warning capabilities, enabling timely identification and response to potential HCAI outbreaks. Syndromic surveillance is highly sensitive and this helps balance the challenge of low sensitivity of laboratory-based surveillance systems. If syndromic surveillance is used hand-in-hand with laboratory-based surveillance systems, it will greatly contribute to establishing the true burden of HAIs in resource-limited settings. Additionally, its flexibility allows for adaptation to different healthcare settings and integration into existing health information systems, facilitating data-driven decision-making and resource allocation. Such a system would augment the event-based surveillance system that is based on alerts and rumours for early detection of events of outbreak potential. If well streamlined and targeted, to monitor priority HCAIs such as surgical site infections, hospital-acquired pneumonia, diarrheal illnesses, the cost and burden of the effects from these infections could be reduced. This approach would offer early detection capabilities and could be expanded into nationwide HCAI surveillance networks with standardised data collection, healthcare worker training, real-time reporting mechanisms, stakeholder collaboration, and continuous monitoring and evaluation. Syndromic surveillance offers a promising strategy for combating HCAIs in LMICs. It provides early warning capabilities, conserves resources, and enhances patient safety. Effective implementation depends on strategic interventions, stakeholder collaboration, and ongoing monitoring and evaluation to ensure sustained effectiveness in HCAI detection and response.

From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England

The purpose of syndromic surveillance is to provide early warning of public health incidents, real-time situational awareness during incidents and emergencies, and reassurance of the lack of impact on the population, particularly during mass gatherings. The United Kingdom Health Security Agency (UKHSA) currently coordinates a real-time syndromic surveillance service that encompasses 6 national syndromic surveillance systems reporting on daily health care usage across England. Each working day, UKHSA analyzes syndromic data from over 200,000 daily patient encounters with the National Health Service, monitoring over 140 unique syndromic indicators, risk assessing over 50 daily statistical exceedances, and taking and recommending public health action on these daily. This English syndromic surveillance service had its origins as a small exploratory pilot in a single region of England in 1999 involving a new pilot telehealth service, initially reporting only on "cold or flu" calls. This pilot showed the value of syndromic surveillance in England, providing advanced warning of the start of seasonal influenza activity over existing laboratory-based surveillance systems. Since this initial pilot, a program of real-time syndromic surveillance has evolved from the single-system, -region, -indicator pilot (using manual data transfer methods) to an all-hazard, multisystem, automated national service. The suite of systems now monitors a wide range of syndromes, from acute respiratory illness to diarrhea to cardiac conditions, and is widely used in routine public health surveillance and for monitoring seasonal respiratory disease and incidents such as the COVID-19 pandemic. Here, we describe the 25-year evolution of the English syndromic surveillance system, focusing on the expansion and improvements in data sources and data management, the technological and digital enablers, and novel methods of data analytics and visualization.

The Implementation of the International Health Regulations on Vector-Borne Diseases: A Scoping Review of the Qualitative Evidence Performed Worldwide

Introduction

The International Health Regulations were created by the World Health Organization with the purpose of preventing the international spread of diseases. The 196 signatory countries are bound by this international agreement. In this article, we conducted a scoping review of the literature concerning the implementation and operationalization of measures at both the continental and national levels to prevent the spread of vector-borne diseases. The purpose was to understand the main strategies and policies adopted, as well as how they have been operating.

Methods

Out of an initial search on PubMed™, SCOPUS™, and Web of Science™ using combinations of "International Health Regulations" and "vector-borne diseases", 75 references were obtained, of which 27 were included after careful qualitative analysis.

Results

Publication dates of included articles ranged from 1996 to 2022. Four major categories of measures were identified: (a) surveillance and epidemic intelligence; (b) Declaration of Public Health Emergency of International Concern; (c) measures in Points of Entry; and (d) vaccination status. Implemented measures were found in all continents: Africa, Oceania (Australia), Asia (China, India, Taiwan), Europe (Ireland, the Netherlands, and Mediterranean countries), North America (USA), and South America (Brazil). Yellow fever, Zika, Dengue, and Chikungunya were the most cited vector-borne diseases but Crimean-Congo hemorrhagic fever, Japanese encephalitis, Lyme disease, Malaria, Leishmaniasis, Tick-borne encephalitis, and West Nile fever were also mentioned.

Conclusion

There are severe asymmetries across countries on the implementation of international regulations with regards to vector-borne diseases, particularly on the issue of surveillance systems. State Parties should consider the lessons learned from the pandemic and perfect their core capacities to prevent future outbreaks of infectious diseases.

Syndromic Surveillance Implementation During Disaster Events

INTRODUCTION

Disease surveillance is an integral part of public health. These systems monitor disease trends and detect outbreaks, whereas they should be evaluated for efficacy. The United States Centres for Disease Control and Prevention publish Guidelines for Evaluating Surveillance Systems to encourage efficient and effective use of public health surveillance that are accepted worldwide.

OBJECTIVE

This study reviews syndromic surveillance during natural and man-made disasters internationally. It aims to (1) review the performance of syndromic surveillance via pre-specified attributes during disaster and to (2) understand its strengths and limitations.

METHODS

PubMed was systematically searched for the articles assessing syndromic surveillance during a disaster. A narrative review was carried out based on those articles. Updated Guidelines for Evaluating Public Health Surveillance Systems were used to review performance of systems.

RESULTS

5,059 studies from PubMed were evaluated, and 16 met inclusion criteria. The majority of these studies considered the implementation of syndromic surveillance useable during disaster events. Studies described systems giving relevant and timely information. Simplicity and timeliness were the most highlighted attributes.

CONCLUSION

Syndromic surveillance is simple, flexible, useful and usable during a disaster. Timely data can be obtained, but the quality of this type of data is sensitive to incomplete and erroneous reporting; because of this, a standardized approach is necessary to optimize these systems.

Comparison of statistical methods for the early detection of disease outbreaks in small population settings

Objectives

This study examines the performance of 6 aberration detection algorithms for the early detection of disease outbreaks in small population settings using syndrome-based early warning surveillance data collected by the Pacific Syndromic Surveillance System (PSSS). Although previous studies have proposed statistical methods for detecting aberrations in larger datasets, there is limited knowledge about how these perform in the presence of small numbers of background cases.

Methods

To address this gap a simulation model was developed to test and compare the performance of the 6 algorithms in detecting outbreaks of different magnitudes, durations, and case distributions.

Results

The study found that while the Early Aberration Reporting System-C1 algorithm developed by Hutwagner et al. outperformed others, no single approach provided reliable monitoring across all outbreak types. Furthermore, aberration detection approaches could only detect very large and acute outbreaks with any reliability.

Conclusion

The findings of this study suggest that algorithm-based approaches to outbreak signal detection perform poorly when applied to settings with small numbers of background cases and should not be relied upon in these contexts. This highlights the need for alternative approaches for accurate and timely outbreak detection in small population settings, particularly those that are resource-constrained.

Comprehensive Vaccine-Preventable Disease Surveillance in the Western Pacific Region: A Literature Review on Integration of Surveillance Functions, 2000-2021

INTRODUCTION

A strategic framework for 2021-2030 developed by the World Health Organization (WHO) Regional Office for the Western Pacific emphasizes the need for high-quality and integrated vaccine-preventable disease (VPD) surveillance. We conducted a literature review to document the barriers, enabling factors, and innovations for integrating surveillance functions for VPDs and other communicable diseases in Western Pacific Region (WPR) countries.

METHODS

We searched published and gray literature on integrated VPD surveillance from 2000 to 2021. Articles in English, Spanish, or French were screened to identify those relating to VPD surveillance in a WPR country and not meeting defined exclusion criteria. We categorized articles using the 8 WHO surveillance support functions and abstracted data on the country; type of surveillance; and reported barriers, enabling factors, and best practices for integration.

RESULTS

Of the 3,137 references screened, 87 met the eligibility criteria. Of the 8 surveillance support functions, the proportion of references that reported integration related to the laboratory was 56%, followed by workforce capacity (54%), governance (51%), data management and use (47%), field logistics and communication (47%), coordination (15%), program management (13%), and supervision (9%). Several references noted fragmented systems and a lack of coordination between units as barriers to integration, highlighting the importance of engagement across public health units and between the public and private sectors. The literature also indicated a need for interoperable information systems and revealed the use of promising new technologies for data reporting and laboratory testing. In some WPR countries, workforce capacity was strengthened at all administrative levels by the implementation of integrated trainings on data monitoring and use and on laboratory techniques applicable to multiple VPDs.

CONCLUSION

This literature review supports integrating VPDs into broader communicable disease surveillance systems in WPR countries while ensuring that the minimal WHO-recommended standards for VPD surveillance are met.

Comparing Vector-Borne Disease Surveillance and Response in Beijing and the Netherlands

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A participatory epidemiological and One Health approach to explore the community’s capacity to detect emerging zoonoses and surveillance network opportunities in the forest region of Guinea

The Ebola virus disease epidemic that threatened West Africa between 2013 and 2016 was of unprecedented health magnitude. After this health crisis, studies highlighted the need to introduce community-based surveillance systems and to adopt a One Health approach. This study aimed to provide preparatory insights for the definition of a community-based surveillance system for emerging zoonoses such as viral hemorrhagic fevers in Guinea. The objective was to explore the disease detection capacity and the surveillance network opportunities at the community level in two pilot areas in the forest region of Guinea, where the epidemic emerged. Based on a participatory epidemiological and One Health approach, we conducted Focus Group Discussions with human, animal and ecosystem health actors. We used a range of participatory tools, included semi-structured interviews, ranking, scoring and flow diagram, to estimate the local knowledge and perception of diseases and clinical signs and to investigate the existing health information exchange network and its related strengths and weaknesses. The results showed that there is heterogeneity in knowledge of diseases and perception of the clinical signs among actors and that there are preferred and more effective health communication channels opportunities. This preparatory study suggests that it is necessary to adapt the case definitions and the health communication channels to the different actors who can play a role in a future community-based surveillance system and provides recommendations for future surveillance activities to be carried out in West Africa.

Viral hemorrhagic diseases have a high risk of emergence in tropical regions. The consequences on public health are often disastrous in the low- and middle-income countries that face difficulties to control epidemics. This scenario has unfortunately occurred in West Africa between 2013 and 2016 with the Ebola virus disease epidemic. There is an urgent need to increase the capacity for rapid detection of the emergence of such diseases and adopting a One Health approach since most of them are zoonotic. Community-based surveillance seems appropriate to address this issue in the context of these countries. We collected preparatory data through semi-structured interviews of community actors in human health, animal health and ecosystem health in Guinea. We used participatory epidemiology that appears to be a consistent method to assess local knowledge and perceptions of diseases and clinical signs and to identify health information exchange network opportunities. We aimed to provide relevant recommendations for the design of adapted case definitions and surveillance network in the prospect of implementing a community-based surveillance system of viral hemorrhagic fevers in Guinea and future surveillance activities to be carried out in West Africa.

Infectious diseases prevention and control using an integrated health big data system in China

BACKGROUND

The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children.

METHODS

IHBDP is composed of medical data from clinics, electronic health records, residents' annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods.

RESULTS

IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones.

CONCLUSIONS

Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods.

Assessment of core and support functions of the communicable disease surveillance system in the Kurdistan Region of Iraq

Early detection and prompt response are crucial measures to prevent and control outbreaks. Public health agencies, therefore, designed the Communicable Disease Surveillance System (CDSS) to obtain essential data instantaneously to be used for appropriate action. However, a periodic evaluation of CDSS is indispensable to ensure the functionality of the system. For this reason, this study aims to assess the performance of the core and support functions of the CDSS in the Kurdistan Region of Iraq. A descriptive cross‐sectional study was used. From a total of 291 health facilities HFs (Primary health care centers and Hospitals) in the Kurdistan region of Iraq that have surveillance activities, 74 HFs were selected using a random stratified sampling approach. The World Health Organization (WHO) generic questionnaire has been used to interview the surveillance staff, together with direct collection of the data. Our analysis shows a lack of surveillance guiding manual in the HFs. Even at the district level, where a surveillance manual existed, case definitions, thresholds, and control measures were still missing. To note, more than 93% of HFs had organized and comprehensive patients registers for the collection of their clinical and secondary data. Also, all HFs had functioning laboratories. The majority of them (almost 93%) were equipped to collect, process, and store blood, stool, and urine specimens. About 72% of these laboratories were also able to transport timely the specimens to more specialized laboratories. At all levels, data reporting to the higher level exceeded the recommended minimum rate of 80%. The reporting system at the district level was based on emails, while in the periphery on hand‐delivered in paper‐based formats (50%), telephone (22%), and social media (22%). Furthermore, our analysis highlights the lack of data analysis: only 3.8% of Primary Health Care Centers conduct simple data analysis regularly, while hospitals do not do any sort of analysis. Also, only a few HFs investigated an outbreak, though using system routine sources to capture these public health events. Our findings show a lack in epidemic preparedness (3%), in feedback (53%), in standard guidelines, training, supervision, and resource allocations in HFs (0%). Taken together, our data show the importance of strengthening the CDSS in the Kurdistan region of Iraq, by reinforcing the surveillance system with continuous feedback, supervision, well‐trained and motivated staff, technical support, and coordination between researchers and physicians.

Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting

BACKGROUND

Automated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, Canada.

METHODS

Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes; chief complaint; discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms.

RESULTS

A daily secure file transfer of Yukon's Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8-89.5% to 62.5-94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset.

CONCLUSIONS

The development and validation of automated ED-SyS in lower-resourced settings can be achieved without sophisticated platforms, intensive resources, time or costs. Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. The use of three different fields and integration of both free-text and structured fields improved case detection.

Using open-source intelligence to identify early signals of COVID-19 in Indonesia

Objective

Open-source data from online news reports and informal sources may provide information about outbreaks before official notification. This study aims to evaluate the use of open-source data from the epidemic observatory, EpiWATCH, to identify the early signals of pneumonia of unknown cause as a proxy for COVID-19 in Indonesia.

Methods

Using open-source data on pneumonia of unknown cause in Indonesia between 1 November 2019 and 31 March 2020 (extracted from EpiWATCH, an open-source epidemic observatory), a descriptive analysis was performed to identify the trend of pneumonia of unknown cause in Indonesia before official notification of COVID-19 cases.

Results

A rise in reports of pneumonia of unknown cause was identified in Indonesia, starting from late January 2020. There were 304 reported cases of pneumonia of unknown cause, 30 of which occurred before the identification of the first COVID-19 cases on 2 March 2020. The early signals of pneumonia of unknown cause in Indonesia may indicate possible unrecognized circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) before official detection.

Discussion

Open-source data may provide rapid, unvalidated information for early detection of outbreaks. Although unvalidated, such information may be used to supplement or trigger investigation and testing. As EpiWATCH sources global information, this methodology can be repeated for other countries within the Western Pacific Region, and for other diseases.

Exploring Vector-Borne Disease Surveillance and Response Systems in Beijing, China: A Qualitative Study from the Health System Perspective

Background: Climate change may contribute to higher incidence and wider geographic spread of vector borne diseases (VBDs). Effective monitoring and surveillance of VBDs is of paramount importance for the prevention of and timely response to outbreaks. Although international regulations exist to support this, barriers and operational challenges within countries hamper efficient monitoring. As a first step to optimise VBD surveillance and monitoring, it is important to gain a deeper understanding of system characteristics and experiences in to date non-endemic regions at risk of becoming endemic in the future. Therefore, this study qualitatively analyses the nature and flexibility of VBD surveillance and response in Beijing. Methods: In this qualitative study, eleven experts working in Beijing’s vector-borne diseases surveillance and response system were interviewed about vector-borne disease surveillance, early warning, response, and strengths and weaknesses of the current approach. Results: Vector-borne disease surveillance occurs using passive syndromic surveillance and separate vector surveillance. Public health authorities use internet reporting networks to determine vector-borne disease risk across Beijing. Response toward a vector-borne disease outbreak is uncommon in this setting due to the currently low occurrence of outbreaks. Conclusions: A robust network of centralised institutions provides the continuity and flexibility needed to adapt and manage possible vector-borne disease threats. Opportunities exist for population-based health promotion and the integration of environment and climate monitoring in vector-borne disease surveillance.

Utility of emergency call centre, dispatch and ambulance data for syndromic surveillance of infectious diseases: a scoping review

BACKGROUND

Syndromic surveillance can supplement conventional health surveillance by analyzing less-specific, near-real-time data for an indication of disease occurrence. Emergency medical call centre dispatch and ambulance data are examples of routinely and efficiently collected syndromic data that might assist in infectious disease surveillance. Scientific literature on the subject is scarce and an overview of results is lacking.

METHODS

A scoping review including (i) review of the peer-reviewed literature, (ii) review of grey literature and (iii) interviews with key informants.

RESULTS

Forty-four records were selected: 20 peer reviewed and 24 grey publications describing 44 studies and systems. Most publications focused on detecting respiratory illnesses or on outbreak detection at mass gatherings. Most used retrospective data; some described outcomes of temporary systems; only two described continuously active dispatch- and ambulance-based syndromic surveillance. Key informants interviewed valued dispatch- and ambulance-based syndromic surveillance as a potentially useful addition to infectious disease surveillance. Perceived benefits were its potential timeliness, standardization of data and clinical value of the data.

CONCLUSIONS

Various dispatch- and ambulance-based syndromic surveillance systems for infectious diseases have been reported, although only roughly half are documented in peer-reviewed literature and most concerned retrospective research instead of continuously active surveillance systems. Dispatch- and ambulance-based syndromic data were mostly assessed in relation to respiratory illnesses; reported use for other infectious disease syndromes is limited. They are perceived by experts in the field of emergency surveillance to achieve time gains in detection of infectious disease outbreaks and to provide a useful addition to traditional surveillance efforts.

High risk for human exposure to Rift Valley fever virus in communities living along livestock movement routes: A cross-sectional survey in Kenya

Introduction

Multiple outbreaks of Rift Valley Fever (RVF) with devastating effects have occurred in East Africa. These outbreaks cause disease in both livestock and humans and affect poor households most severely. Communities living in areas practicing nomadic livestock movement may be at higher risk of infection. This study sought to i) determine the human exposure to Rift Valley fever virus (RVFV) in populations living within nomadic animal movement routes in Kenya; and ii) identify risk factors for RVFV infection in these communities.

Methods

A cross-sectional descriptive study design was used. Samples were collected from the year 2014 to 2015 in a community-based sampling exercise involving healthy individuals aged ≥18 years from Isiolo, Tana River, and Garissa counties. In total, 1210 samples were screened by ELISA for the presence of immunoglobulin IgM and IgG antibodies against RVFV. Positive results were confirmed by plaque reduction neutralization test.

Results

Overall, IgM and IgG prevalence for all sites combined was 1.4% (95% CI 0.8–2.3%) and 36.4% (95% CI 33.8–39.2%), respectively. Isiolo County recorded a non-significant higher IgG prevalence of 38.8% than Garissa 35.9% and Tana River 32.2% (Chi square = 2.5, df = 2, p = 0.287). Males were significantly at higher risk of infection by RVFV than females (OR = 1.67, 95% CI 1.17–2.39, p<0.005). Age was significantly associated with RVFV infection (Wald Chi = 94.2, df = 5, p<0.0001). Individuals who had regular contact with cattle (OR = 1.38, 95%CI 1.01–1.89) and donkeys (OR = 1.38, 95%CI 1.14–1.67), or contact with animals through birthing (OR = 1.69, 95%CI 1.14–2.51) were significantly at a greater risk of RVFV infection than those who did not.

Conclusion

This study demonstrated that although the Isiolo County has been classified as being at medium risk for RVF, virus infection appeared to be as prevalent in humans as in Tana River and Garissa, which have been classified as being at high risk. Populations in these counties live within nomadic livestock movement routes and therefore at risk of being exposed to the RVFV. Interventions to control RVFV infections therefore, should target communities living along livestock movement pathways.

Rift Valley fever (RVF) is a neglected mosquito-borne zoonotic disease that causes major outbreaks and economic harm to human and ruminants health leading to increased poverty within affected communities. RVF is caused by RVF virus (RVFV) affecting humans and a wide range of ruminants. The virus is transmitted through bites from mosquitoes and exposure to blood, body fluids, or tissues of infected ruminants. It was first isolated in Kenya in 1930 and several outbreaks have been recorded in many countries in sub-Saharan Africa. We studied pastoralist communities living along livestock migratory routes. Migratory livestock do move long distances in search of water and pasture and may be at higher risk of exposure to RVFV. We also determined risk factors for RVFV infection by studying age, gender, contact with animals through birthing, and occupation. Prevention and control of RVFV infection can target significant risk factors to prevent spread and re-occurrence of outbreaks.

A real-time spatio-temporal syndromic surveillance system with application to small companion animals

Lack of disease surveillance in small companion animals worldwide has contributed to a deficit in our ability to detect and respond to outbreaks. In this paper we describe the first real-time syndromic surveillance system that conducts integrated spatio-temporal analysis of data from a national network of veterinary premises for the early detection of disease outbreaks in small animals. We illustrate the system’s performance using data relating to gastrointestinal disease in dogs and cats. The data consist of approximately one million electronic health records for dogs and cats, collected from 458 UK veterinary premises between March 2014 and 2016. For this illustration, the system predicts the relative reporting rate of gastrointestinal disease amongst all presentations, and updates its predictions as new data accrue. The system was able to detect simulated outbreaks of varying spatial geometry, extent and severity. The system is flexible: it generates outcomes that are easily interpretable; the user can set their own outbreak detection thresholds. The system provides the foundation for prompt detection and control of health threats in companion animals.

Valuing Health Surveillance as an Information System: Interdisciplinary Insights

The economic evaluation of health surveillance systems and of health information is a methodological challenge, as for information systems in general. Main present threads are considering cost-effectiveness solutions, minimizing costs for a given technically required output, or cost-benefit analysis, balancing costs with economic benefits of duly informed public interventions. The latter option, following a linear command-and-control perspective, implies considering a main causal link between information, decision, action, and health benefits. Yet, valuing information, taking into account its nature and multiple sources, the modalities of its processing cycle, from production to diffusion, decentralized use and gradual building of a shared information capital, constitutes a promising challenge. This work proposes an interdisciplinary insight on the value of health surveillance to get a renewed theoretical framework integrating information and informatics theory and information economics. The reflection is based on a typological approach of value, basically distinguishing between use and non-use values. Through this structured discussion, the main idea is to expand the boundaries of surveillance evaluation, to focus on changes and trends, on the dynamic and networked structure of information systems, on the contribution of diverse data, and on the added value of combining qualitative and quantitative information. Distancing itself from the command-and-control model, this reflection considers the behavioral fundaments of many health risks, as well as the decentralized, progressive and deliberative dimension of decision-making in risk management. The framework also draws on lessons learnt from recent applications within and outside of health sector, as in surveillance of antimicrobial resistance, inter-laboratory networks, the use of big data or web sources, the diffusion of technological products and large-scale financial risks. Finally, the paper poses the bases to think the challenge of a workable approach to economic evaluation of health surveillance through a better understanding of health information value. It aims to avoid over-simplifying the range of health information benefits across society while keeping evaluation within the boundaries of what may be ascribed to the assessed information system.

Syndromic survey and molecular analysis of influenza viruses at the human-swine interface in two West African cosmopolitan cities suggest the possibility of bidirectional interspecies transmission

Influenza viruses are frequently transmitted between pigs and their handlers, and among pig handlers. However, reports on socio-environmental variables as potential risk factors associated with transmission of influenza in West African swine production facilities are very scarce. Syndromic survey for influenza was therefore conducted in Ibadan, Nigeria, and Kumasi, Ghana, in order to identify and elucidate selected socio-environmental variables that may contribute to the occurrence and distribution of influenza-like illness (ILI) among swine industry workers. In addition, molecular analyses were conducted to elucidate the nature of influenza viruses circulating at the human-swine interface in these cities and better understand the dynamics of their transmission. Influenza viruses were detected by type-specific and subtype-specific RT-PCR. Sequencing and phylogenetic analyses were carried out. Socio-environmental variables were tested by both univariable and multivariable regression methods for significance at p < 0.05. Three risk factors for ILI were identified in each city. These included "frequency of visit of pig handler to pig pen or lairage" (Ibadan: risk ratio [RR] = 1.54, 95% confidence interval [CI] = 1.36-1.79, p = 0.02; Kumasi: RR = 1.28, 95% CI = 1.11-1.71, p = 0.01) and "pig handler's awareness about biosecurity measures" (Ibadan: RR = 7.09, 95% CI = 2.36-21.32, p < 0.001; Kumasi: RR = 4.84, 95% CI = 1.98-11.80, p < 0.001). Influenza A(H1N1)pdm09 viruses, with M genes closely related to those which circulated among pigs in the two cities during the same period, were detected among Nigerian and Ghanaian pig industry workers. These findings suggest the possibility of bidirectional transmission of influenza at the human-swine interface in these cities and underscore the need for more extensive molecular studies. Risk factors identified may assist in the control of human-to-human and human-to-swine transmission of influenza in the West African swine industry.

Epidemic surveillance in a low resource setting: lessons from an evaluation of the Solomon Islands syndromic surveillance system, 2017

Background

Solomon Islands is one of the least developed countries in the world. Recognising that timely detection of outbreaks is needed to enable early and effective response to disease outbreaks, the Solomon Islands government introduced a simple syndromic surveillance system in 2011. We conducted the first evaluation of the system and the first exploration of a national experience within the broader multi-country Pacific Syndromic Surveillance System to determine if it is meeting its objectives and to identify opportunities for improvement.

Methods

We used a multi-method approach involving retrospective data collection and statistical analysis, modelling, qualitative research and observational methods.

Results

We found that the system was well accepted, highly relied upon and designed to account for contextual limitations. We found the syndromic algorithm used to identify outbreaks was moderately sensitive, detecting 11.8% (IQR: 6.3–25.0%), 21.3% (IQR: 10.3–36.8%), 27.5% (IQR: 12.8–52.3%) and 40.5% (IQR: 13.5–65.7%) of outbreaks that caused small, moderate, large and very large increases in case presentations to health facilities, respectively. The false alert rate was 10.8% (IQR: 4.8–24.5%). Rural coverage of the system was poor. Limited workforce, surveillance resourcing and other ‘upstream’ health system factors constrained performance.

Conclusions

The system has made a significant contribution to public health security in Solomon Islands, but remains insufficiently sensitive to detect small-moderate sized outbreaks and hence should not be relied upon as a stand-alone surveillance strategy. Rather, the system should sit within a complementary suite of early warning surveillance activities including event-based, in-patient- and laboratory-based surveillance methods. Future investments need to find a balance between actions to address the technical and systems issues that constrain performance while maintaining simplicity and hence sustainability.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6295-7) contains supplementary material, which is available to authorized users.

Towards effective outbreak detection: a qualitative study to identify factors affecting nurses' early warning surveillance practice in Solomon Islands

Background

Intelligence generated by a surveillance system is dependent on the quality of data that are collected. We investigated the knowledge, attitudes and practices of nurses responsible for outbreak early warning surveillance data collection in Solomon Islands to identify factors that influence their ability to perform surveillance-related tasks with rigour.

Methods

We interviewed 12 purposively selected surveillance nurses and conducted inductive analysis on resulting data.

Results

Interviewees were knowledgeable and willing to contribute to the surveillance system. Constraining factors included the perception that surveillance was less important than patient care and could be ‘deferred’ during busy periods and wide variability in the application of case definitions. Motivating factors were frequent in-clinic training, formal recognition for good performance, incentives and designation of a focal point. Nurses held mixed views about the effect of mobile technologies on surveillance practice.

Conclusions

This study identified several challenges to consistent and accurate data collection and reporting. Engagement of different parts of the health system, including human resources and health facilities’ management, is needed to address these challenges.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3508-9) contains supplementary material, which is available to authorized users.

Pit Latrines: A Noninvasive Sampling Strategy to Assess Fecal Pathogen Occurrence in Low Resource Communities

Limited understanding of disease in low resource communities continues to hamper improvements in health. We evaluated household pit latrine sampling as a non-invasive approach to investigate important fecal pathogens such as Giardia lamblia and Cryptosporidium spp. in impoverished communities where health-seeking behavior limits the sensitivity of health facility-based surveillance. Fecal samples were collected from pit latrines in randomly selected households and from patients presenting to the only hospital in the region during the same time periods. Samples were tested with a commercially available ELISA. Giardia household prevalence was 28.7% in 2016 and 48.4% in 2017, while individual samples from hospital submission had a Giardia prevalence of 2.4% in 2016 and 8.0% in 2017. Cryptosporidium was only found in one household. Results suggest that pit latrine surveillance for fecal-borne infections provide course estimates of community infection levels that are unbiased by health seeking behaviors and allow surveillance of vulnerable sectors of a population.

Cracking the Code: Using Data to Combat the Opioid Crisis

The goal of this article is to understand the value of data and to call for efforts to explore improved data sharing and collection among local, state, and federal agencies. It discusses the data available and existing barriers to sharing it. It also looks at examples of data sharing initiatives and analysis, such as mapping and visualization tools. The article then examines relevant regulations and calls for reforms. Finally, the article considers objections, including privacy interests, data security, and the costs and benefits of data sharing initiatives.

Enhanced surveillance for Rift Valley Fever in livestock during El Niño rains and threat of RVF outbreak, Kenya, 2015-2016

Background

In mid-2015, the United States’ Pandemic Prediction and Forecasting Science and Technical Working Group of the National Science and Technology Council, Food and Agriculture Organization Emergency Prevention Systems, and Kenya Meteorological Department issued an alert predicting a high possibility of El-Niño rainfall and Rift Valley Fever (RVF) epidemic in Eastern Africa.

Methodology/Principal findings

In response to the alert, the Kenya Directorate of Veterinary Services (KDVS) carried out an enhanced syndromic surveillance system between November 2015 and February 2016, targeting 22 RVF high-risk counties in the country as identified previously through risk mapping. The surveillance collected data on RVF-associated syndromes in cattle, sheep, goats, and camels from >1100 farmers through 66 surveillance officers. During the 14-week surveillance period, the KDVS received 10,958 reports from participating farmers and surveillance officers, of which 362 (3.3%) had at least one syndrome. The reported syndromes included 196 (54.1%) deaths in young livestock, 133 (36.7%) abortions, and 33 (9.1%) hemorrhagic diseases, with most occurring in November and December, the period of heaviest rainfall. Of the 69 herds that met the suspect RVF herd definition (abortion in flooded area), 24 (34.8%) were defined as probable (abortions, mortalities in the young ones, and/or hemorrhagic signs) but none were confirmed.

Conclusion/Significance

This surveillance activity served as an early warning system that could detect RVF disease in animals before spillover to humans. It was also an excellent pilot for designing and implementing syndromic surveillance in animals in the country, which is now being rolled out using a mobile phone-based data reporting technology as part of the global health security system.

Occurrence of Rift Valley Fever (RVF) outbreak is associated with heavy El-Niño rainfall. In July 2015, an alert on the likelihood of El-Niño rainfall and RVF outbreak in Eastern Africa region was issued by the United States, Food and Agriculture Organization, and Kenya Meteorological Department. In response to the alert, the Kenya Directorate of Veterinary Services (KDVS) carried out an enhanced syndromic surveillance system between November 2015 and February 2016 in the 22 counties that had previously been identified as RVF high-risk counties. The surveillance system collected data on RVF-associated syndromes and risk factors in cattle, sheep, goats and camels from more than 1100 farmers. Of the 10,958 field reports submitted, 45 were consistent with suspect RVF disease and 24 of these identified as probable RVF, triggering an immediate response. Whereas investigations of the suspect cases and laboratory testing did not confirm RVF cases, the surveillance system served as an excellent early warning system that could detect disease in animal before spillover to humans.

Systematic review of electronic surveillance of infectious diseases with emphasis on antimicrobial resistance surveillance in resource-limited settings

BACKGROUND

Electronic surveillance of infectious diseases involves rapidly collecting, collating, and analyzing vast amounts of data from interrelated multiple databases. Although many developed countries have invested in electronic surveillance for infectious diseases, the system still presents a challenge for resource-limited health care settings.

METHODS

We conducted a systematic review by performing a comprehensive literature search on MEDLINE (January 2000-December 2015) to identify studies relevant to electronic surveillance of infectious diseases. Study characteristics and results were extracted and systematically reviewed by 3 infectious disease physicians.

RESULTS

A total of 110 studies were included. Most surveillance systems were developed and implemented in high-income countries; less than one-quarter were conducted in low-or middle-income countries. Information technologies can be used to facilitate the process of obtaining laboratory, clinical, and pharmacologic data for the surveillance of infectious diseases, including antimicrobial resistance (AMR) infections. These novel systems require greater resources; however, we found that using electronic surveillance systems could result in shorter times to detect targeted infectious diseases and improvement of data collection.

CONCLUSIONS

This study highlights a lack of resources in areas where an effective, rapid surveillance system is most needed. The availability of information technology for the electronic surveillance of infectious diseases, including AMR infections, will facilitate the prevention and containment of such emerging infectious diseases.

Lessons learnt from implementation of the International Health Regulations: a systematic review

Objective

To respond to the World Health Assembly call for dissemination of lessons learnt from countries that have begun implementing the International Health Regulations, 2005 revision; IHR (2005).

Methods

In November 2015, we conducted a systematic search of the following online databases and sources: PubMed®, Embase®, Global Health, Scopus, World Health Organization (WHO) Global Index Medicus, WHO Bulletin on IHR Implementation and the International Society for Disease Surveillance. We included identified studies and reports summarizing national experience in implementing any of the IHR (2005) core capacities or their components. We excluded studies that were theoretical or referred to IHR (1969). Qualitative systematic review methodology, including meta-ethnography, was used for qualitative synthesis.

Findings

We analysed 51 articles from 77 countries representing all WHO Regions. The meta-syntheses identified a total of 44 lessons learnt across the eight core capacities of IHR (2005). Major themes included the need to mobilize and sustain political commitment; to adapt global requirements based on local sociocultural, epidemiological, health system and economic contexts; and to conduct baseline and follow-up assessments to monitor the status of IHR (2005) implementation.

Conclusion

Although experiences of IHR (2005) implementation covered a wide global range, more documentation from Africa and Eastern Europe is needed. We did not find specific areas of weakness in monitoring IHR (2005); sustained monitoring of all core capacities is required to ensure effective systems. These lessons learnt could be adapted by countries in the process of meeting IHR (2005) requirements.

Human-Wildlife Interactions Predict Febrile Illness in Park Landscapes of Western Uganda

Fevers of unknown origin complicate treatment and prevention of infectious diseases and are a global health burden. We examined risk factors of self-reported fever-categorized as "malarial" and "nonmalarial"-in households adjacent to national parks across the Ugandan Albertine Rift, a biodiversity and emerging infectious disease hotspot. Statistical models fitted to these data suggest that perceived nonmalarial fevers of unknown origin were associated with more frequent direct contact with wildlife and with increased distance from parks where wildlife habitat is limited to small forest fragments. Perceived malarial fevers were associated with close proximity to parks but were not associated with direct wildlife contact. Self-reported fevers of any kind were not associated with livestock ownership. These results suggest a hypothesis that nonmalarial fevers in this area are associated with wildlife contact, and further investigation of zoonoses from wildlife is warranted. More generally, our findings of land use-disease relationships aid in hypothesis development for future research in this social-ecological system where emerging infectious diseases specifically, and rural public health provisioning generally, are important issues.

Online surveillance of media health event reporting in Nepal: digital disease detection from a One Health perspective

Background

Traditional media and the internet are crucial sources of health information. Media can significantly shape public opinion, knowledge and understanding of emerging and endemic health threats. As digital communication rapidly progresses, local access and dissemination of health information contribute significantly to global disease detection and reporting.

Methods

Health event reports in Nepal (October 2013–December 2014) were used to characterize Nepal’s media environment from a One Health perspective using HealthMap - a global online disease surveillance and mapping tool. Event variables (location, media source type, disease or risk factor of interest, and affected species) were extracted from HealthMap.

Results

A total of 179 health reports were captured from various sources including newspapers, inter-government agency bulletins, individual reports, and trade websites, yielding 108 (60%) unique articles. Human health events were reported most often (n = 85; 79%), followed by animal health events (n = 23; 21%), with no reports focused solely on environmental health.

Conclusions

By expanding event coverage across all of the health sectors, media in developing countries could play a crucial role in national risk communication efforts and could enhance early warning systems for disasters and disease outbreaks.

Verification of Neonatal Tetanus Surveillance Systems in Katsina State, Nigeria

Background:

The incidence and mortality rates of neonatal tetanus (NNT) remain underreported in Nigeria. The goal of the study was to compare the NNT prevalence and the mortality rates from the existing surveillance system and active surveillance of health facility records in 7 selected health facilities from 2010 to 2014 in Katsina State, Nigeria.

Methods:

The study is a retrospective record review using extracted data from NNT records and analyzed using descriptive statistics.

Results:

The prevalence of NNT and mortality rate were 336 cases and 3.4 deaths per 100 000 population, respectively, whereas the prevalence of NNT and mortality rate reported through the Integrated Disease Surveillance and Response (IDSR) system were 111 cases and 1.0 death per 100 000 population, respectively.

Conclusion:

The study shows underreporting of NNT in the existing IDSR system.

Implications:

Active surveillance is a good strategy for verifying underreporting of NNT in the surveillance system. The IDSR system should be strengthened with the capacity to detect events associated with a disease toward global elimination.

Outbreak detection and evaluation of a school-based influenza-like-illness syndromic surveillance in Tianjin, China

School-based influenza-like-illness (ILI) syndromic surveillance can be an important part of influenza community surveillance by providing early warnings for outbreaks and leading to a fast response. From September 2012 to December 2014, syndromic surveillance of ILI was carried out in 4 county-level schools. The cumulative sum methods(CUSUM) was used to detect abnormal signals. A susceptible-exposed-infectious/asymptomatic-recovered (SEIAR) model was fit to the influenza outbreak without control measures and compared with the actual influenza outbreak to evaluate the effectiveness of early control efforts. The ILI incidence rates in 2014 (14.51%) was higher than the incidence in 2013 (5.27%) and 2012 (3.59%). Ten school influenza outbreaks were detected by CUSUM. Each outbreak had high transmissibility with a median R_unc of 4.62. The interventions in each outbreak had high effectiveness and all R_con were 0. The early intervention had high effectiveness within the school-based ILI syndromic surveillance. Syndromic surveillance within schools can play an important role in controlling influenza outbreaks.

Foodborne Disease and the Need for Greater Foodborne Disease Surveillance in the Caribbean

The Caribbean is a net importer of food, and with billions of dollars’ worth of food products being imported each year, territorial governments are now seeking to encourage local production of foods in an attempt to stem the loss of foreign exchange from these economies with little resilience. The Caribbean, however, lacks the comprehensive food safety system that should be a corollary to successful food production. Regional authorities underestimate the burden of foodborne diseases especially on its workforce and major economic base, the tourism industry. Anecdotally after every mass event in the region, many officially unreported cases of gastroenteritis are recognized. This short communication makes the argument of the importance of food borne illnesses specific to the Caribbean, and improvements that could be made to surveillance to reduce negative outcomes associated with the food supply chain.

Predictors of Neonatal Tetanus Mortality in Katsina State, Northwestern Nigeria

Background

The mortality rate of neonatal tetanus (NNT) remains high in Nigeria. The study was guided by Mosley and Chen's model for the elements of child survival in developing countries. The goal of the study was to assess the associations between selected NNT risk factors, number of maternal tetanus toxoid injections, frequency of antenatal visits, place of delivery, and cord care with neonatal mortality as the outcome variable.

Methods

The study is a retrospective record review using data from 332 NNT records and analyzed using a logistic regression model.

Findings

Neonates whose mothers had 1 dose of tetanus toxoid vaccine were found to be 4% less prone to NNT mortality compared to neonates whose mothers did not have any dose of tetanus toxoid vaccine during pregnancy (P < .05, odds ratio = 4.12, 95% confidence interval = 1.04-16.29. Frequency of antenatal visits, place of delivery, and cord care were all not significant predictors of NNT mortality.

Conclusion

The study shows that there is association between NNT risk factors and neonatal mortality, hence the need to further strengthen the NNT surveillance system for early detection of potential risk factors. This would help develop specific public health interventions aimed at improving the outcome of NNT.

Implications

The identification and analysis of NNT mortality risk factors and promoting tetanus toxoid vaccination among pregnant women are effective strategies toward attaining NNT elimination goals in Nigeria.

Bed bugs and possible transmission of human pathogens: a systematic review

The global population of bed bugs (Cimex lectularius and Cimex hemipterus, family Cimicidae) has undergone a significant resurgence since the late 1990s. This is likely due to an increase in global travel, trade, and the number of insecticide-resistant bed bugs. The global bed bug population is estimated to be increasing by 100-500 % annually. The worldwide spread of bed bugs is concerning, because they are a significant socioeconomic burden and a major concern to public health. According to the United States Environmental Protection Agency, bed bugs are "a pest of significant health importance." Additionally, 68 % of U.S. pest professionals reported that bed bugs are the most challenging pest to treat. Upwards of 45 disease pathogens have been reported in bed bugs. Recent studies report that bed bugs may be competent vectors for pathogens, such as Bartonella quintana and Trypanosoma cruzi. However, public health reports have thus far failed to produce evidence that major infectious disease outbreaks have been associated with bed bugs. Since many disease pathogens have previously been reported in bed bugs and the worldwide bed bug population is now drastically increasing, it stands to reason to wonder if bed bugs might transmit human pathogens. This review includes a literature search on recently published clinical and laboratory studies (1990-2016) investigating bed bugs as potential vectors of infectious disease, and reports the significant findings and limitations of the reviewed studies. To date, no published study has demonstrated a causal relationship between bed bugs and infectious disease transmission in humans. Also, we present and propose to expand on previous hypotheses as to why bed bugs do not transmit human pathogens. Bed bugs may contain "neutralizing factors" that attenuate pathogen virulence and, thereby, decrease the ability of bed bugs to transmit infectious disease.

Surveillance systems for sexually transmitted infections: a global review

PURPOSE OF REVIEW

Sexually transmitted infections (STIs) continue to exert a substantial public health burden globally but surveillance remains a challenge, especially in the developing world. We reviewed STI surveillance systems in various regions globally and used available data to provide an overview of recent trends in STI epidemiology.

RECENT FINDINGS

STI surveillance systems in the developing world are often limited and restricted to ad hoc cross-sectional surveys; however, available data suggest that these areas are disproportionately affected by STIs, with a higher burden in marginalized groups such as sex workers. Developed countries typically have established surveillance systems. Recent reports suggest many of these countries are experiencing rising diagnoses of STIs in men who have sex with men (MSM) and an increasing contribution of HIV-positive MSM to STI epidemics.

SUMMARY

There is considerable variability in the surveillance for STIs globally, ranging from active or passive, to sentinel, laboratory or clinic-based systems. Given different levels of resources and patterns of healthcare provision, it is difficult to compare surveillance data across regions; however, available data suggest that considerable inequality in STI burden exists. In resource-limited settings, syndromic surveillance with periodic laboratory assessments is recommended to monitor trends in STIs.

SCM: a practical tool to implement hospital-based syndromic surveillance

BACKGROUND

Syndromic surveillance has been widely used for the early warning of infectious disease outbreaks, especially in mass gatherings, but the collection of electronic data on symptoms in hospitals is one of the fundamental challenges that must be overcome during operating a syndromic surveillance system. The objective of our study is to describe and evaluate the implementation of a symptom-clicking-module (SCM) as a part of the enhanced hospital-based syndromic surveillance during the 41st World Exposition in Shanghai, China, 2010.

METHODS

The SCM, including 25 targeted symptoms, was embedded in the sentinels' Hospital Information Systems (HIS). The clinicians used SCM to record these information of all the visiting patients, and data were collated and transmitted automatically in daily batches. The symptoms were categorized into seven targeted syndromes using pre-defined criteria, and statistical algorithms were applied to detect temporal aberrations in the data series.

RESULTS

SCM was deployed successfully in each sentinel hospital and was operated during the 184-day surveillance period. A total of 1,730,797 patient encounters were recorded by SCM, and 6.1 % (105,352 visits) met the criteria of the seven targeted syndromes. Acute respiratory and gastrointestinal syndromes were reported most frequently, accounted for 92.1 % of reports in all syndromes, and the aggregated time-series presented an obvious day-of-week variation over the study period. In total, 191 aberration signals were triggered, and none of them were identified as outbreaks after verification and field investigation.

CONCLUSIONS

SCM has acted as a practical tool for recording symptoms in the hospital-based enhanced syndromic surveillance system during the 41st World Exposition in Shanghai, in the context of without a preexisting electronic tool to collect syndromic data in the HIS of the sentinel hospitals.

Assessing Commitment and Reporting Fidelity to a Text Message-Based Participatory Surveillance in Rural Western Uganda

Syndromic surveillance, the collection of symptom data from individuals prior to or in the absence of diagnosis, is used throughout the developed world to provide rapid indications of outbreaks and unusual patterns of disease. However, the low cost of syndromic surveillance also makes it highly attractive for the developing world. We present a case study of electronic participatory syndromic surveillance, using participant-mobile phones in a rural region of Western Uganda, which has a high infectious disease burden, and frequent local and regional outbreaks. Our platform uses text messages to encode a suite of symptoms, their associated durations, and household disease burden, and we explore the ability of participants to correctly encode their symptoms, with an average of 75.2% of symptom reports correctly formatted between the second and 11th reporting timeslots. Concomitantly we identify divisions between participants able to rapidly adjust to this unusually participatory style of data collection, and those few for whom the study proved more challenging. We then perform analyses of the resulting syndromic time series, examining the clustering of symptoms by time and household to identify patterns such as a tendency towards the within-household sharing of respiratory illness.

Early warning epidemic surveillance in the Pacific island nations: an evaluation of the Pacific syndromic surveillance system

OBJECTIVE

The Pacific Syndromic Surveillance System (PSSS), launched in 2010, provides a simple mechanism by which 121 sentinel surveillance sites in 21 Pacific island countries and areas perform routine indicator- and event-based surveillance for the early detection of infectious disease outbreaks. This evaluation aims to assess whether the PSSS is meeting its objectives, what progress has been made since a formative evaluation of the system was conducted in 2011, and provides recommendations to enhance the PSSS's performance in the future.

METHODS

Twenty-one informant interviews were conducted with national operators of the system and regional public health agencies that use information generated by it. Historic PSSS data were analysed to assess timeliness and completeness of reporting.

RESULTS

The system is simple, acceptable and useful for public health decision-makers. The PSSS has greatly enhanced Pacific island countries' ability to undertake early warning surveillance and has contributed to efforts to meet national surveillance-related International Health Regulation (2005) capacity development obligations. Despite this, issues with timeliness and completeness of reporting, data quality and system stability persist.

CONCLUSION

A balance between maintaining the system's simplicity and technical advances will need to be found to ensure its long-term sustainability, given the low-resource context for which it is designed.

Syndromic surveillance in companion animals utilizing electronic medical records data: development and proof of concept

In an effort to recognize and address communicable and point-source epidemics in dog and cat populations, this project created a near real-time syndromic surveillance system devoted to companion animal health in the United States. With over 150 million owned pets in the US, the development of such a system is timely in light of previous epidemics due to various causes that were only recognized in retrospect. The goal of this study was to develop epidemiologic and statistical methods for veterinary hospital-based surveillance, and to demonstrate its efficacy by detection of simulated foodborne outbreaks using a database of over 700 hospitals. Data transfer protocols were established via a secure file transfer protocol site, and a data repository was constructed predominantly utilizing open-source software. The daily proportion of patients with a given clinical or laboratory finding was contrasted with an equivalent average proportion from a historical comparison period, allowing construction of the proportionate diagnostic outcome ratio and its confidence interval for recognizing aberrant heath events. A five-tiered alert system was used to facilitate daily assessment of almost 2,000 statistical analyses. Two simulated outbreak scenarios were created by independent experts, blinded to study investigators, and embedded in the 2010 medical records. Both outbreaks were detected almost immediately by the alert system, accurately detecting species affected using relevant clinical and laboratory findings, and ages involved. Besides demonstrating proof-in-concept of using veterinary hospital databases to detect aberrant events in space and time, this research can be extended to conducting post-detection etiologic investigations utilizing exposure information in the medical record.

Measuring costs of data collection at village clinics by village doctors for a syndromic surveillance system-a cross sectional survey from China

BACKGROUND

Studies into the costs of syndromic surveillance systems are rare, especially for estimating the direct costs involved in implementing and maintaining these systems. An Integrated Surveillance System in rural China (ISSC project), with the aim of providing an early warning system for outbreaks, was implemented; village clinics were the main surveillance units. Village doctors expressed their willingness to join in the surveillance if a proper subsidy was provided. This study aims to measure the costs of data collection by village clinics to provide a reference regarding the subsidy level required for village clinics to participate in data collection.

METHODS

We conducted a cross-sectional survey with a village clinic questionnaire and a staff questionnaire using a purposive sampling strategy. We tracked reported events using the ISSC internal database. Cost data included staff time, and the annual depreciation and opportunity costs of computers. We measured the village doctors' time costs for data collection by multiplying the number of full time employment equivalents devoted to the surveillance by the village doctors' annual salaries and benefits, which equaled their net incomes. We estimated the depreciation and opportunity costs of computers by calculating the equivalent annual computer cost and then allocating this to the surveillance based on the percentage usage.

RESULTS

The estimated total annual cost of collecting data was 1,423 Chinese Renminbi (RMB) in 2012 (P25 = 857, P75 = 3284), including 1,250 RMB (P25 = 656, P75 = 3000) staff time costs and 134 RMB (P25 = 101, P75 = 335) depreciation and opportunity costs of computers.

CONCLUSIONS

The total costs of collecting data from the village clinics for the syndromic surveillance system was calculated to be low compared with the individual net income in County A.

The enigmatic nodding syndrome outbreak in northern Uganda: an analysis of the disease burden and national response strategies

To date, the cause of nodding syndrome (NS) remains unknown; however, efforts continue to establish risk factors and optimal symptomatic treatments. We documented the burden and national response strategies including involvement of key stakeholders in the management of the NS epidemic in order to inform future interventions against epidemics of undetermined aetiology. Data were collected through semi-structured interviews with selected leaders in the affected districts and at the Ministry of Health, and through review of documents. We participated in and analysed the proceedings of the first international scientific conference on NS held in Kampala in August 2012. We then analysed the chronology of the NS notification and the steps undertaken in the response plan. Over 3000 children have been affected by NS in northern Uganda; with an estimated case fatality of 6.7%. The first cases of NS were reported in 1997 in internally displaced people's camps in Kitgum district; however, response efforts by the Ministry of Health and partners towards understanding the disorder and establish management only commenced in 2009. Key strategies in response to the NS epidemic have included formation of a national and district task forces, development of training manual on NS and training of primary healthcare professionals on case diagnosis and clinical management, establishment of treatment and rehabilitation centres, surveillance and promotion of researches to further inform management of the syndrome.

Resilient information networks for coordination of foodborne disease outbreaks

Foodborne disease outbreaks are increasingly being seen as a greater concern by public health authorities. It has also become a global research agenda to identify improved pathways to coordinating outbreak detection. Furthermore, a significant need exists for timely coordination of the detection of potential foodborne disease outbreaks to reduce the number of infected individuals and the overall impact on public health security. This study aimed to offer an effective approach for coordinating foodborne disease outbreaks. First, we identify current coordination processes, complexities, and challenges. We then explore social media surveillance strategies, usage, and the power of these strategies to influence decision-making. Finally, based on informal (social media) and formal (organizational) surveillance approaches, we propose a hybrid information network model for improving the coordination of outbreak detection.

Collecting syndromic surveillance data by mobile phone in rural India: implementation and feasibility

Background

Infectious disease surveillance has long been a challenge for countries like India, where 75% of the health care services are private and consist of both formal and informal health care providers. Infectious disease surveillance data are regularly collected from governmental and qualified private facilities, but not from the informal sector. This study describes a mobile-based syndromic surveillance system and its application in a resource-limited setting, collecting data on patients’ symptoms from formal and informal health care providers.

Design

The study includes three formal and six informal health care providers from two districts of Madhya Pradesh, India. Data collectors were posted in the clinics during the providers’ working hours and entered patient information and infectious disease symptoms on the mobile-based syndromic surveillance system.

Results

Information on 20,424 patients was collected in the mobile-based surveillance system. The five most common (overlapping) symptoms were fever (48%), cough (38%), body ache (38%), headache (37%), and runny nose (22%). During the same time period, the government's disease surveillance program reported around 22,000 fever cases in one district as a whole. Our data – from a very small fraction of all health care providers – thus highlight an enormous underreporting in the official surveillance data, which we estimate here to capture less than 1% of the fever cases. Additionally, we found that patients from more than 600 villages visited the nine providers included in our study.

Conclusions

The study demonstrated that a mobile-based system can be used for disease surveillance from formal and informal providers in resource-limited settings. People who have not used smartphones or even computers previously can, in a short timeframe, be trained to fill out surveillance forms and submit them from the device. Technology, including network connections, works sufficiently for disease surveillance applications in rural parts of India. The data collected may be used to better understand the health-seeking behaviour of those visiting informal providers, as they do not report through any official channels. We also show that the underreporting to the government can be enormous.

Evaluation of outbreak detection performance using multi-stream syndromic surveillance for influenza-like illness in rural Hubei Province, China: a temporal simulation model based on healthcare-seeking behaviors

BACKGROUND

Syndromic surveillance promotes the early detection of diseases outbreaks. Although syndromic surveillance has increased in developing countries, performance on outbreak detection, particularly in cases of multi-stream surveillance, has scarcely been evaluated in rural areas.

OBJECTIVE

This study introduces a temporal simulation model based on healthcare-seeking behaviors to evaluate the performance of multi-stream syndromic surveillance for influenza-like illness.

METHODS

Data were obtained in six towns of rural Hubei Province, China, from April 2012 to June 2013. A Susceptible-Exposed-Infectious-Recovered model generated 27 scenarios of simulated influenza A (H1N1) outbreaks, which were converted into corresponding simulated syndromic datasets through the healthcare-behaviors model. We then superimposed converted syndromic datasets onto the baselines obtained to create the testing datasets. Outbreak performance of single-stream surveillance of clinic visit, frequency of over the counter drug purchases, school absenteeism, and multi-stream surveillance of their combinations were evaluated using receiver operating characteristic curves and activity monitoring operation curves.

RESULTS

In the six towns examined, clinic visit surveillance and school absenteeism surveillance exhibited superior performances of outbreak detection than over the counter drug purchase frequency surveillance; the performance of multi-stream surveillance was preferable to signal-stream surveillance, particularly at low specificity (Sp <90%).

CONCLUSIONS

The temporal simulation model based on healthcare-seeking behaviors offers an accessible method for evaluating the performance of multi-stream surveillance.

Detecting disease outbreaks in mass gatherings using Internet data

BACKGROUND

Mass gatherings, such as music festivals and religious events, pose a health care challenge because of the risk of transmission of communicable diseases. This is exacerbated by the fact that participants disperse soon after the gathering, potentially spreading disease within their communities. The dispersion of participants also poses a challenge for traditional surveillance methods. The ubiquitous use of the Internet may enable the detection of disease outbreaks through analysis of data generated by users during events and shortly thereafter.

OBJECTIVE

The intent of the study was to develop algorithms that can alert to possible outbreaks of communicable diseases from Internet data, specifically Twitter and search engine queries.

METHODS

We extracted all Twitter postings and queries made to the Bing search engine by users who repeatedly mentioned one of nine major music festivals held in the United Kingdom and one religious event (the Hajj in Mecca) during 2012, for a period of 30 days and after each festival. We analyzed these data using three methods, two of which compared words associated with disease symptoms before and after the time of the festival, and one that compared the frequency of these words with those of other users in the United Kingdom in the days following the festivals.

RESULTS

The data comprised, on average, 7.5 million tweets made by 12,163 users, and 32,143 queries made by 1756 users from each festival. Our methods indicated the statistically significant appearance of a disease symptom in two of the nine festivals. For example, cough was detected at higher than expected levels following the Wakestock festival. Statistically significant agreement (chi-square test, P<.01) between methods and across data sources was found where a statistically significant symptom was detected. Anecdotal evidence suggests that symptoms detected are indeed indicative of a disease that some users attributed to being at the festival.

CONCLUSIONS

Our work shows the feasibility of creating a public health surveillance system for mass gatherings based on Internet data. The use of multiple data sources and analysis methods was found to be advantageous for rejecting false positives. Further studies are required in order to validate our findings with data from public health authorities.