Evaluating surveillance strategies for the early detection of low pathogenicity avian influenza infections

In recent years, the early detection of low pathogenicity avian influenza (LPAI) viruses in poultry has become increasingly important, given their potential to mutate into highly pathogenic viruses. However, evaluations of LPAI surveillance have mainly focused on prevalence and not on the ability to act as an early warning system. We used a simulation model based on data from Italian LPAI epidemics in turkeys to evaluate different surveillance strategies in terms of their performance as early warning systems. The strategies differed in terms of sample size, sampling frequency, diagnostic tests, and whether or not active surveillance (i.e., routine laboratory testing of farms) was performed, and were also tested under different epidemiological scenarios. We compared surveillance strategies by simulating within-farm outbreaks. The output measures were the proportion of infected farms that are detected and the farm reproduction number (R(h)). The first one provides an indication of the sensitivity of the surveillance system to detect within-farm infections, whereas R(h) reflects the effectiveness of outbreak detection (i.e., if detection occurs soon enough to bring an epidemic under control). Increasing the sampling frequency was the most effective means of improving the timeliness of detection (i.e., it occurs earlier), whereas increasing the sample size increased the likelihood of detection. Surveillance was only effective in preventing an epidemic if actions were taken within two days of sampling. The strategies were not affected by the quality of the diagnostic test, although performing both serological and virological assays increased the sensitivity of active surveillance. Early detection of LPAI outbreaks in turkeys can be achieved by increasing the sampling frequency for active surveillance, though very frequent sampling may not be sustainable in the long term. We suggest that, when no LPAI virus is circulating yet and there is a low risk of virus introduction, a less frequent sampling approach might be admitted, provided that the surveillance is intensified as soon as the first outbreak is detected.     

Application of control measures for infections caused by multi-resistant gram-negative bacteria in intensive care unit patients

Multi-resistant gram-negative rods are important pathogens in intensive care units (ICU), cause high rates of mortality, and need infection control measures to avoid spread to another patients. This study was undertaken prospectively with all of the patients hospitalized at ICU, Anesthesiology of the Hospital S?o Paulo, using the ICU component of the National Nosocomial Infection Surveillance System (NNIS) methodology, between March 1, 1997 and June 30, 1998. Hospital infections occurring during the first three months after the establishment of prevention and control measures (3/1/97 to 5/31/97) were compared to those of the last three months (3/1/98 to 5/31/98). In this period, 933 NNIS patients were studied, with 139 during the first period and 211 in the second period. The overall rates of infection by multi-resistant microorganisms in the first and second periods were, respectively, urinary tract infection: 3.28/1000 patients/day; 2.5/1000 patients/day; pneumonia: 2.10/1000 patients/day; 5.0/1000 patients/day; bloodstream infection: 1.09/1000 patients/day; 2.5/1000 patients/day. A comparison between overall infection rates of both periods (Wilcoxon test) showed no statistical significance (p = 0.067). The use of intervention measures effectively decreased the hospital bloodstream infection rate (p < 0.001), which shows that control measures in ICU can contribute to preventing hospital infections.     

Case Based Measles Surveillance in Pune: Evidence to Guide Current and Future Measles Control and Elimination Efforts in India

Background

According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011) are reported here with wider implications for measles elimination efforts in India.

Methods

Standard protocols were followed for case identification, investigation and classification. Suspected measles cases were confirmed through serology (IgM) or epidemiological linkage or clinical presentation. Data regarding age, sex, vaccination status were collected and annualized incidence rates for measles and rubella cases calculated.

Results

Of the 1011 suspected measles cases reported to the surveillance system, 76% were confirmed measles, 6% were confirmed rubella, and 17% were non-measles, non-rubella cases. Of the confirmed measles cases, 95% were less than 15 years of age. Annual measles incidence rate was more than 250 per million persons and nearly half were associated with outbreaks. Thirty-nine per cent of the confirmed measles cases were vaccinated with one dose of measles vaccine (MCV1).

Conclusion

Surveillance demonstrated high measles incidence and frequent outbreaks in Pune where MCV1 coverage in infants was above 90%. Results indicate that even high coverage with a single dose of measles vaccine was insufficient to provide population protection and prevent measles outbreaks. An effective measles and rubella surveillance system provides essential information to plan, implement and evaluate measles immunization strategies and monitor progress towards measles elimination.     

Estimating the Effectiveness of Early Control Measures through School Absenteeism Surveillance in Observed Outbreaks at Rural Schools in Hubei,China

Background

School absenteeism is a common data source in syndromic surveillance, which allows for the detection of outbreaks at an early stage. Previous studies focused on its correlation with other data sources. In this study, we evaluated the effectiveness of control measures based on early warning signals from school absenteeism surveillance in rural Chinese schools.

Methods

A school absenteeism surveillance system was established in all 17 primary schools in 3 adjacent towns in the Chinese region of Hubei. Three outbreaks (varicella, mumps, and influenza-like illness) were detected and controlled successfully from April 1, 2012, to January 15, 2014. An impulse susceptible-exposed-infectious-recovered model was used to fit the epidemics of these three outbreaks. Moreover, it simulated the potential epidemics under interventions resulting from traditional surveillance signals. The effectiveness of the absenteeism-based control measures was evaluated by comparing the simulated datasets.

Results

The school absenteeism system generated 52 signals. Three outbreaks were verified through epidemiological investigation. Compared to traditional surveillance, the school absenteeism system generated simultaneous signals for the varicella outbreak, but 3 days in advance for the mumps outbreak and 2–4 days in advance for the influenza-like illness outbreak. The estimated excess protection rates of control measures based on early signals were 0.0%, 19.0–44.1%, and 29.0–37.0% for the three outbreaks, respectively.

Conclusions

Although not all outbreak control measures can benefit from early signals through school absenteeism surveillance, the effectiveness of early signal-based interventions is obvious. School absenteeism surveillance plays an important role in reducing outbreak spread.     

Cost-Analysis of Seven Nosocomial Outbreaks in an Academic Hospital

Objectives

Nosocomial outbreaks, especially with (multi-)resistant microorganisms, are a major problem for health care institutions. They can cause morbidity and mortality for patients and controlling these costs substantial amounts of funds and resources. However, how much is unclear. This study sets out to provide a comparable overview of the costs of multiple outbreaks in a single academic hospital in the Netherlands.

Methods

Based on interviews with the involved staff, multiple databases and stored records from the Infection Prevention Division all actions undertaken, extra staff employment, use of resources, bed-occupancy rates, and other miscellaneous cost drivers during different outbreaks were scored and quantified into Euros. This led to total costs per outbreak and an estimated average cost per positive patient per outbreak day.

Results

Seven outbreaks that occurred between 2012 and 2014 in the hospital were evaluated. Total costs for the hospital ranged between €10,778 and €356,754. Costs per positive patient per outbreak day, ranged between €10 and €1,369 (95% CI: €49-€1,042), with a mean of €546 and a median of €519. Majority of the costs (50%) were made because of closed beds.

Conclusions

This analysis is the first to give a comparable overview of various outbreaks, caused by different microorganisms, in the same hospital and all analyzed with the same method. It shows a large variation within the average costs due to different factors (e.g. closure of wards, type of ward). All outbreaks however cost considerable amounts of efforts and money (up to €356,754), including missed revenue and control measures.     

Results from the First 12 Months of the National Surveillance of Healthcare Associated Outbreaks in Germany, 2011/2012

Background

In August 2011, the German Protection against Infection Act was amended, mandating the reporting of healthcare associated infection (HAI) outbreak notifications by all healthcare workers in Germany via local public health authorities and federal states to the Robert Koch Institute (RKI).

Objective

To describe the reported HAI-outbreaks and the surveillance system’s structure and capabilities.

Methods

Information on each outbreak was collected using standard paper forms and notified to RKI. Notifications were screened daily and regularly analysed.

Results

Between November 2011 and November 2012, 1,326 paper forms notified 578 HAI-outbreaks, between 7 and 116 outbreaks per month. The main causative agent was norovirus (n = 414/578; 72%). Among the 108 outbreaks caused by bacteria, the most frequent pathogens were Clostridium difficile (25%) Klebsiella spp. (19%) and Staphylococcus spp. (19%). Multidrug-resistant bacteria were responsible for 54/108 (50%) bacterial outbreaks. Hospitals were affected most frequently (485/578; 84%). Hospital outbreaks due to bacteria were mostly reported from intensive care units (ICUs) (45%), followed by internal medicine wards (16%).

Conclusion

The mandatory HAI-outbreak surveillance system describes common outbreaks. Pathogens with a particular high potential to cause large or severe outbreaks may be identified, enabling us to further focus research and preventive measures. Increasing the sensitivity and reliability of the data collection further will facilitate identification of outbreaks able to increase in size and severity, and guide specific control measures to interrupt their propagation.     

Surveillance for Yellow Fever Virus in Non-Human Primates in Southern Brazil, 2001–2011: A Tool for Prioritizing Human Populations for Vaccination

In Brazil, epizootics among New World monkey species may indicate circulation of yellow fever (YF) virus and provide early warning of risk to humans. Between 1999 and 2001, the southern Brazilian state of Rio Grande do Sul initiated surveillance for epizootics of YF in non-human primates to inform vaccination of human populations. Following a YF outbreak, we analyzed epizootic surveillance data and assessed YF vaccine coverage, timeliness of implementation of vaccination in unvaccinated human populations. From October 2008 through June 2009, circulation of YF virus was confirmed in 67 municipalities in Rio Grande do Sul State; vaccination was recommended in 23 (34%) prior to the outbreak and in 16 (24%) within two weeks of first epizootic report. In 28 (42%) municipalities, vaccination began more than two weeks after first epizootic report. Eleven (52%) of 21 laboratory-confirmed human YF cases occurred in two municipalities with delayed vaccination. By 2010, municipalities with confirmed YF epizootics reported higher vaccine coverage than other municipalities that began vaccination. In unvaccinated human populations timely response to epizootic events is critical to prevent human yellow fever cases.     

Early detection of tuberculosis outbreaks among the San Francisco homeless: trade-offs between spatial resolution and temporal scale

Background

San Francisco has the highest rate of tuberculosis (TB) in the U.S. with recurrent outbreaks among the homeless and marginally housed. It has been shown for syndromic data that when exact geographic coordinates of individual patients are used as the spatial base for outbreak detection, higher detection rates and accuracy are achieved compared to when data are aggregated into administrative regions such as zip codes and census tracts. We examine the effect of varying the spatial resolution in the TB data within the San Francisco homeless population on detection sensitivity, timeliness, and the amount of historical data needed to achieve better performance measures.

Methods and Findings

We apply a variation of space-time permutation scan statistic to the TB data in which a patient''s location is either represented by its exact coordinates or by the centroid of its census tract. We show that the detection sensitivity and timeliness of the method generally improve when exact locations are used to identify real TB outbreaks. When outbreaks are simulated, while the detection timeliness is consistently improved when exact coordinates are used, the detection sensitivity varies depending on the size of the spatial scanning window and the number of tracts in which cases are simulated. Finally, we show that when exact locations are used, smaller amount of historical data is required for training the model.

Conclusion

Systematic characterization of the spatio-temporal distribution of TB cases can widely benefit real time surveillance and guide public health investigations of TB outbreaks as to what level of spatial resolution results in improved detection sensitivity and timeliness. Trading higher spatial resolution for better performance is ultimately a tradeoff between maintaining patient confidentiality and improving public health when sharing data. Understanding such tradeoffs is critical to managing the complex interplay between public policy and public health. This study is a step forward in this direction.     

急诊重症监护病房耐甲氧西林金黄色葡萄球菌定植与感染调查分析

目的 调查急诊重症监护病房( EICU)耐甲氧西林金黄色葡萄球菌(MRSA)定植与感染状况,为实时控制医院感染暴发流行提供参考依据.方法 对临床资料进行分析,环境卫生学监测采样方法参照卫生部《消毒技术规范》,制定干预措施.结果 6例MRSA定植和感染病例平均年龄62.5岁,原发性基础疾病重;41份环境标本和16份来自接触阳性患者的医务人员手部标本中均分离到病原菌,阳性率分别为24.39％和18.75％.结论MRSA定植是造成医院感染的源头,将仅出现定植的病例并入感染病例进行统计分析,可实时监控院内医院感染的暴发.     

耐甲氧西林金黄色葡萄球菌的分布及耐药性分析

目的分析医院耐甲氧西林金黄色葡萄球菌（MRSA）的分布及耐药情况,为临床治疗金黄色葡萄球菌医院感染提供科学依据。方法对618株金黄色葡萄球菌进行常规鉴定,用K—B法对其进行药敏试验。结果5年MRSA的平均检出率为51．9％（321／618）,MRSA感染高发主要科室为ICU、神经外科、神经内科,MRSA检出率前三位的科室为神经外科（84．1％）、ICU（76．3％）、呼吸内科（61．3％）,标本来源主要为痰液,占67．3％,检出率82．4％。MRSA对万古霉素、替考拉宁、利奈唑胺保持100％敏感,对氯霉素、米诺环素、复方新诺明等的耐药率较低,对其他药物都保持了65％以上的高耐药率。结论对重点科室监控,合理使用抗生素,严格执行无菌操作,采取有效的消毒隔离,尽量减少侵袭性操作等措施是控制并减少MRSA感染的重要环节。     

Surveillance considerations for malaria elimination

ABSTRACT: Constant malaria monitoring and surveillance systems have been highlighted as critical for malaria elimination. The absence of robust monitoring and surveillance systems able to respond to outbreaks in a timely manner undeniably contributed to the failure of the last global attempt to eradicate malaria. Today, technological advances could allow for rapid detection of focal outbreaks and improved deployment of diagnostic and treatment supplies to areas needing support. However, optimizing diffusion activities (e.g., distributing vector controls and medicines, as well as deploying behaviour change campaigns) requires networks of diverse scholars to monitor, learn, and evaluate data and multiple organizations to coordinate their intervention activities. Surveillance systems that can gather, store and process information, from communities to national levels, in a centralized, widely accessible system will allow tailoring of surveillance and intervention efforts. Different systems and, thus reactions, will be effective in different endemic, geographical or socio-cultural contexts. Investing in carefully designed monitoring technologies, built for a multiple-acter, dynamic system, will help to improve malaria elimination efforts by improving the coordination, timing, coverage, and deployment of malaria technologies.     

Syndromic Surveillance for Local Outbreaks of Lower-Respiratory Infections: Would It Work?

Background

Although syndromic surveillance is increasingly used to detect unusual illness, there is a debate whether it is useful for detecting local outbreaks. We evaluated whether syndromic surveillance detects local outbreaks of lower-respiratory infections (LRIs) without swamping true signals by false alarms.

Methods and Findings

Using retrospective hospitalization data, we simulated prospective surveillance for LRI-elevations. Between 1999–2006, a total of 290762 LRIs were included by date of hospitalization and patients place of residence (>80% coverage, 16 million population). Two large outbreaks of Legionnaires disease in the Netherlands were used as positive controls to test whether these outbreaks could have been detected as local LRI elevations. We used a space-time permutation scan statistic to detect LRI clusters. We evaluated how many LRI-clusters were detected in 1999–2006 and assessed likely causes for the cluster-signals by looking for significantly higher proportions of specific hospital discharge diagnoses (e.g. Legionnaires disease) and overlap with regional influenza elevations. We also evaluated whether the number of space-time signals can be reduced by restricting the scan statistic in space or time. In 1999–2006 the scan-statistic detected 35 local LRI clusters, representing on average 5 clusters per year. The known Legionnaires'' disease outbreaks in 1999 and 2006 were detected as LRI-clusters, since cluster-signals were generated with an increased proportion of Legionnaires disease patients (p:<0.0001). 21 other clusters coincided with local influenza and/or respiratory syncytial virus activity, and 1 cluster appeared to be a data artifact. For 11 clusters no likely cause was defined, some possibly representing as yet undetected LRI-outbreaks. With restrictions on time and spatial windows the scan statistic still detected the Legionnaires'' disease outbreaks, without loss of timeliness and with less signals generated in time (up to 42% decline).

Conclusions

To our knowledge this is the first study that systematically evaluates the performance of space-time syndromic surveillance with nationwide high coverage data over a longer period. The results show that syndromic surveillance can detect local LRI-outbreaks in a timely manner, independent of laboratory-based outbreak detection. Furthermore, since comparatively few new clusters per year were observed that would prompt investigation, syndromic hospital-surveillance could be a valuable tool for detection of local LRI-outbreaks.     

Use of the internet to enhance infectious disease surveillance and outbreak investigation

Modernization of electronic communication systems to facilitate infectious disease surveillance and outbreak investigation became a priority after the 2001 anthrax attacks. However, the extent to which communicable disease investigators are using web-based information resources, e-mail notifications, or secure information exchange systems to facilitate surveillance is unknown. To address this question, we conducted a survey in 2004 of state and local communicable disease investigators responsible for infectious disease surveillance and outbreak investigation in three states. The majority (70.7%) of the 297 respondents accessed the Internet for information regarding infectious disease surveillance and outbreaks at least weekly. Most (74%) respondents who searched for information from the Centers for Disease Control and Prevention (CDC) website reported that they found what they were looking for 75-100% of the time, compared with 54% who found the information from their state health department websites 75-100% of the time. One-third of respondents read e-mail notifications regarding outbreaks under investigation in their state less frequently than monthly; 34% of those enrolled in CDC's Epidemic Information Exchange (Epi-X) read e-mail notifications of new reports less frequently than monthly. Forty-seven (18%) respondents read ProMED-mail at least monthly, while 46% indicated they had never consulted MEDLINE/PubMed. Some progress has been made in use of the Internet to facilitate communication in infectious disease surveillance and outbreak investigation. Addressing barriers to access and usability of new information systems in conjunction with training and technical support could enhance infectious disease surveillance and timely investigation of outbreaks and bioterrorism events.     

Electronic outbreak surveillance in Germany: a first evaluation for nosocomial norovirus outbreaks

Background

In Germany, surveillance for infectious disease outbreaks is integrated into an electronic surveillance system. For 2007, the national surveillance database contains case-based information on 201,224 norovirus cases, three-quarters of which are linked to outbreaks. We evaluated the data quality of the national database in reflecting nosocomial norovirus outbreak (NNO) data available in 19 Hessian local public health authorities (LPHAs) and the influence of differences between LPHA''s follow-up procedures for laboratory notifications of Norovirus positive stool samples on outbreak underascertainment.

Methods

Data on NNO beginning in 2007 and notified to the 19 LPHAs were extracted from the national database, investigated regarding internal validity and compared to data collected from LPHAs for a study on NNO control. LPHAs were questioned whether they routinely contacted all persons for whom a laboratory diagnosis of norovirus infection was notified. The number of outbreaks per 1,000 hospital beds and the number of cases within NNOs for acute care and rehabilitation hospitals were compared between counties with and without complete follow-up.

Results

The national database contained information on 155 NNOs, including 3,115 cases. Cases were missed in the national database in 58 (37%) of the outbreaks. Information on hospitalisation was incorrect for an estimated 47% of NNO cases. Information on county of infection was incorrect for 24% (199/820) of cases being forwarded between LPHAs for data entry. Reported NNO incidence and number of NNO cases in acute care hospitals was higher in counties with complete follow-up (incidence-rate ratio (IRR) 2.7, 95% CI 1.4–5.7, p-value 0.002 and IRR 2.1, 95% CI 1.9–2.4, p-value 0.001, respectively).

Conclusions

Many NNOs are not notified by hospitals and differences in LPHA procedures have an impact on the number of outbreaks captured in the surveillance system. Forwarding of case-by-case data on Norovirus outbreak cases from the local to the state and national level should not be required.     

Diagnostic capacity for viral haemorrhagic septicaemia virus (VHSV) infection in rainbow trout (Oncorhynchus mykiss) is greatly increased by combining viral isolation with specific antibody detection

Detection of disease specific antibodies in farmed rainbow trout (Oncorhynchus mykiss) has been proposed as an alternative or supplement to the currently approved procedures for diagnosis and surveillance in this species. In samples from natural outbreaks of the disease viral haemorrhagic septicaemia (VHS) at two freshwater farms in southern Denmark serologic testing was used to broaden the diagnostic window from outbreak to diagnosis in the laboratory as compared to traditional procedures of isolation and identification of the virus. The serologic assay clearly increased the chance of detecting present or previous infections where the pathogen could not be isolated by standard methods (indicating older infections where the virus had been cleared). Our data allowed us to monitor the levels of neutralising antibodies in relation to the presence of the virus in fish experiencing two different types of outbreaks at two different farms. By sequence analysis of the viral glycoprotein from selected isolates we found no evidence for escape mutants having developed in the fish showing high titres of neutralising antibodies.     

Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records

We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.     

Outbreaks of salmonella infection in hospitals in England and Wales 1978-87.

A total of 248 outbreaks of salmonella infection in hospital affecting over 3000 patients and 110 associated deaths were ascertained in England and Wales in 1978-87, compared with 522 outbreaks of salmonella in 1968-77. The largest reduction was found in outbreaks from children''s units and maternity units. Fifty seven (24%) outbreaks were considered to be due to foodborne salmonellosis, and 70 (30%) were reported as person to person spread of the infection. The psychiatric hospital was the type of hospital in which foodborne outbreaks most often occurred, but the risk of being affected in an outbreak not due to food seemed to be highest in maternity units. Better control of infection and better surveillance should lead to earlier investigation and control of outbreaks.     

The Impact of Inadequate Terminal Disinfection on an Outbreak of Imipenem-Resistant Acinetobacter baumannii in an Intensive Care Unit

Background

This study was conducted to investigate an outbreak caused by imipenem-resistant Acinetobacter baumannii (IRAB) in a medical intensive care unit (ICU) in a regional hospital.

Methods

In response to an IRAB outbreak from October 2012 to February 2013, we developed several infection control measures, including an extensive review process of environmental cleaning and disinfection, and used molecular methods to identify each clinical and environmental IRAB isolate.

Results

During this five-month period, 22 patients were colonized with IRAB and 18 patients had IRAB infections. The in-hospital mortality rate was significantly higher among patients with infections rather than colonizations (44.4% vs 9.1%, p = 0.028). Additionally, nine environmental specimens, including five specimens collected after terminal disinfection, were positive for IRAB. 12 environmental isolates and 28 of 36 available clinical isolates belonged to one unique pulsotype A, which was confirmed by molecular methods. We found the concentration of disinfectant, 0.08% sodium hypochlorite, was inadequate. After correcting the environmental cleansing methods, the surveillance study showed no further IRAB isolates on the control panel surfaces of the medical equipment or in patients in the ICU. Additionally, an in vitro study of IRAB immersed in different concentrations of sodium hypochlorite showed that 0.5% sodium hypochlorite eradicates IRAB after 30 seconds of inoculation, but 0.08% sodium hypochlorite only reduces the bacterial load.

Conclusions

This study highlights the importance of the preparation of disinfectants to adequately achieve environmental disinfection in the control of IRAB outbreaks in the ICU.     

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.