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.     

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.     

ISS-An Electronic Syndromic Surveillance System for Infectious Disease in Rural China

Background

syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings.

Objective

this study describes the design and pilot implementation of an electronic surveillance system (ISS) for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system.

Methods

ISS was developed based on an existing platform ‘Crisis Information Sharing Platform’ (CRISP), combining with modern communication and GIS technology. ISS has four interconnected functions: 1) work group and communication group; 2) data source and collection; 3) data visualization; and 4) outbreak detection and alerting.

Results

As of Jan. 31^st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74256, 79701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level.

Conclusions

The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China.     

Demonstrating the Use of High-Volume Electronic Medical Claims Data to Monitor Local and Regional Influenza Activity in the US

Introduction

Fine-grained influenza surveillance data are lacking in the US, hampering our ability to monitor disease spread at a local scale. Here we evaluate the performances of high-volume electronic medical claims data to assess local and regional influenza activity.

Material and Methods

We used electronic medical claims data compiled by IMS Health in 480 US locations to create weekly regional influenza-like-illness (ILI) time series during 2003–2010. IMS Health captured 62% of US outpatient visits in 2009. We studied the performances of IMS-ILI indicators against reference influenza surveillance datasets, including CDC-ILI outpatient and laboratory-confirmed influenza data. We estimated correlation in weekly incidences, peak timing and seasonal intensity across datasets, stratified by 10 regions and four age groups (<5, 5–29, 30–59, and 60+ years). To test IMS-Health performances at the city level, we compared IMS-ILI indicators to syndromic surveillance data for New York City. We also used control data on laboratory-confirmed Respiratory Syncytial Virus (RSV) activity to test the specificity of IMS-ILI for influenza surveillance.

Results

Regional IMS-ILI indicators were highly synchronous with CDC''s reference influenza surveillance data (Pearson correlation coefficients rho≥0.89; range across regions, 0.80–0.97, P<0.001). Seasonal intensity estimates were weakly correlated across datasets in all age data (rho≤0.52), moderately correlated among adults (rho≥0.64) and uncorrelated among school-age children. IMS-ILI indicators were more correlated with reference influenza data than control RSV indicators (rho = 0.93 with influenza v. rho = 0.33 with RSV, P<0.05). City-level IMS-ILI indicators were highly consistent with reference syndromic data (rho≥0.86).

Conclusion

Medical claims-based ILI indicators accurately capture weekly fluctuations in influenza activity in all US regions during inter-pandemic and pandemic seasons, and can be broken down by age groups and fine geographical areas. Medical claims data provide more reliable and fine-grained indicators of influenza activity than other high-volume electronic algorithms and should be used to augment existing influenza surveillance systems.     

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

Background

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea.

Methods

Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson''s correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons.

Results

The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05).

Conclusions

In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.     

Exploratory Analysis of Methods for Automated Classification of Laboratory Test Orders into Syndromic Groups in Veterinary Medicine

Background

Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users.

Methods

This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory.

Results

High performance (F₁-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F_1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F_1-macro), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F_1-micro score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F_1-micro = 0.994 and F_1-macro = .955), however the classification process is not transparent to the domain experts.

Conclusion

The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish automated methods to update model rules without user input.     

The Incidence and Clinical Burden of Respiratory Syncytial Virus Disease Identified through Hospital Outpatient Presentations in Kenyan Children

Background

There is little information that describe the burden of respiratory syncytial virus (RSV) associated disease in the tropical African outpatient setting.

Methods

We studied a systematic sample of children aged <5 years presenting to a rural district hospital in Kenya with acute respiratory infection (ARI) between May 2002 and April 2004. We collected clinical data and screened nasal wash samples for RSV antigen by immunofluorescence. We used a linked demographic surveillance system to estimate disease incidence.

Results

Among 2143 children tested, 166 (8%) were RSV positive (6% among children with upper respiratory tract infection and 12% among children with lower respiratory tract infection (LRTI). RSV was more likely in LRTI than URTI (p<0.001). 51% of RSV cases were aged 1 year or over. RSV cases represented 3.4% of hospital outpatient presentations. Relative to RSV negative cases, RSV positive cases were more likely to have crackles (RR = 1.63; 95% CI 1.34–1.97), nasal flaring (RR = 2.66; 95% CI 1.40–5.04), in-drawing (RR = 2.24; 95% CI 1.47–3.40), fast breathing for age (RR = 1.34; 95% CI 1.03–1.75) and fever (RR = 1.54; 95% CI 1.33–1.80). The estimated incidence of RSV-ARI and RSV-LRTI, per 100,000 child years, among those aged <5 years was 767 and 283, respectively.

Conclusion

The burden of childhood RSV-associated URTI and LRTI presenting to outpatients in this setting is considerable. The clinical features of cases associated with an RSV infection were more severe than cases without an RSV diagnosis.     

Pneumococci in the African Meningitis Belt: Meningitis Incidence and Carriage Prevalence in Children and Adults

Background

The development of optimal vaccination strategies for pneumococcal conjugate vaccines requires serotype-specific data on disease incidence and carriage prevalence. This information is lacking for the African meningitis belt.

Methods

We conducted hospital-based surveillance of acute bacterial meningitis in an urban and rural population of Burkina Faso during 2007–09. Cerebrospinal fluid was evaluated by polymerase chain reaction for species and serotype. In 2008, nasopharyngeal swabs were obtained from a representative population sample (1 month to 39 years; N = 519) and additional oropharyngeal swabs from 145 participants. Swabs were evaluated by culture.

Results

Annual pneumococcal meningitis incidence rates were highest among <6-month-old (58/100,000) and 15- to 19-year-old persons (15/100,000). Annual serotype 1 incidence was around 5/100,000 in all age groups. Pneumococcal carriage prevalence in nasopharyngeal swabs was 63% among <5-year-old children and 22% among ≥5-year-old persons, but adding oropharyngeal to nasopharyngeal swabs increased the estimated carriage prevalence by 60%. Serotype 1 showed high propensity for invasive disease, particularly among persons aged ≥5 years.

Conclusions

Serotype 1 causes the majority of cases with a relatively constant age-specific incidence. Pneumococcal carriage is common in all age groups including adults. Vaccination programs in this region may need to include older target age groups for optimal impact on disease burden.     

Epidemiology of Zoonotic Hepatitis E: A Community-Based Surveillance Study in a Rural Population in China

Background

Hepatitis E is caused by two viral genotype groups: human types and zoonotic types. Current understanding of the epidemiology of the zoonotic hepatitis E disease is founded largely on hospital-based studies.

Methods

The epidemiology of hepatitis E was investigated in a community-based surveillance study conducted over one year in a rural city in eastern China with a registered population of 400,162.

Results

The seroprevalence of hepatitis E in the cohort was 38%. The incidence of hepatitis E was 2.8/10,000 person-years. Totally 93.5% of the infections were attributed to genotype 4 and the rest, to genotype 1. Hepatitis E accounted for 28.4% (102/359) of the acute hepatitis cases and 68.9% (102/148) of the acute viral hepatitis cases in this area of China. The disease occurred sporadically with a higher prevalence during the cold season and in men, with the male-to-female ratio of 3∶1. Additionally, the incidence of hepatitis E increased with age. Hepatitis B virus carriers have an increased risk of contracting hepatitis E than the general population (OR = 2.5, 95%CI 1.5–4.2). Pre-existing immunity to hepatitis E lowered the risk (relative risk  = 0.34, 95% CI 0.21–0.55) and reduced the severity of the disease.

Conclusions

Hepatitis E in the rural population of China is essentially that of a zoonosis due to the genotype 4 virus, the epidemiology of which is similar to that due to the other zoonotic genotype 3 virus.     

Utilization of Surveillance after Polypectomy in the Medicare Population – A Cohort Study

Background

Surveillance in patients with previous polypectomy was underused in the Medicare population in 1994. This study investigates whether expansion of Medicare reimbursement for colonoscopy screening in high-risk individuals has reduced the inappropriate use of surveillance.

Methods

We used Kaplan-Meier analysis to estimate time to surveillance and polyp recurrence rates for Medicare beneficiaries with a colonoscopy with polypectomy between 1998 and 2003 who were followed through 2008 for receipt of surveillance colonoscopy. Generalized Estimating Equations were used to estimate risk factors for: 1) failing to undergo surveillance and 2) polyp recurrence among these individuals. Analyses were stratified into three 2-year cohorts based on baseline colonoscopy date.

Results

Medicare beneficiaries undergoing a colonoscopy with polypectomy in the 1998–1999 (n = 4,136), 2000–2001 (n = 3,538) and 2002–2003 (n = 4,655) cohorts had respective probabilities of 30%, 26% and 20% (p<0.001) of subsequent surveillance events within 3 years. At the same time, 58%, 52% and 45% (p<0.001) of beneficiaries received a surveillance event within 5 years. Polyp recurrence rates after 5 years were 36%, 30% and 26% (p<0.001) respectively. Older age (≥ 70 years), female gender, later cohort (2000–2001 & 2002–2003), and severe comorbidity were the most important risk factors for failure to undergo a surveillance event. Male gender and early cohort (1998–1999) were the most important risk factors for polyp recurrence.

Conclusions

Expansion of Medicare reimbursement for colonoscopy screening in high-risk individuals has not reduced underutilization of surveillance in the Medicare population. It is important to take action now to improve this situation, because polyp recurrence is substantial in this population.     

Prevalence and Factors Associated with Herpes Simplex Virus Type 2 Infection in Patients Attending a Baltimore City Emergency Department

Objectives

Herpes simplex virus type 2 (HSV-2) is a common sexually transmitted disease, but there is limited data on its epidemiology among urban populations. The urban Emergency Department (ED) is a potential venue for surveillance as it predominantly serves an inner city minority population. We evaluate the seroprevalence and factors associated with HSV-2 infection among patients attending the Johns Hopkins Hospital Adult Emergency Department (JHH ED).

Methods

An identity unlinked-serosurvey was conducted between 6/2007 and 9/2007 in the JHH ED; sera were tested by the Focus HerpeSelect ELISA. Prevalence risk ratios (PRR) were used to determine factors associated with HSV-2 infection.

Results

Of 3,408 serum samples, 1,853 (54.4%) were seropositive for HSV-2. Females (adjPRR  = 1.47, 95% CI 1.38–1.56), non-Hispanic blacks (adjPRR  = 2.03, 95% CI 1.82–2.27), single (adjPRR  = 1.15, 95% CI 1.07–1.25), divorced (adjPRR  = 1.28, 95% CI 1.15–1.41), and unemployed patients (adjPRR  = 1.13, 95% CI 1.05–1.21) had significantly higher rates of HSV-2 infection. Though certain zip codes had significantly higher seroprevalence of HSV-2, this effect was completely attenuated when controlling for age and gender.

Conclusions

Seroprevalence of HSV-2 in the JHH ED was higher than U.S. national estimates; however, factors associated with HSV-2 infection were similar. The high seroprevalence of HSV-2 in this urban ED highlights the need for targeted testing and treatment. Cross-sectional serosurveys in the urban ED may help to examine the epidemiology of HSV-2.     

Improved Completion Rates and Characterization of Drug Reactions with an Intensive Chagas Disease Treatment Program in Rural Bolivia

Background

Chagas disease treatment is limited by drug availability, adverse side effect profiles of available medications, and poor adherence.

Methods

Adult Chagas disease patients initiating 60-days of benznidazole were randomized to weekly or twice-weekly evaluations of medication adherence and screening for adverse drug events (ADEs). Mid-week evaluations employed phone-based evaluations. Adherence was measured by self-report, pill counts with intentional over-distribution, and Medication Event Monitoring Systems (MEMS). Prospective data were compared to historical controls treated with benznidazole at the same hospital.

Results

162 prospective patients were compared to 172 historical patients. Pill counts correlated well with MEMS data (R = 0.498 for 7-day intervals, R = 0.872 for intervals >7 days). Treatment completion rates were higher among prospective than historical patients (82.1% vs. 65.1%), primarily due to lower abandonment rates. Rates of ADEs were lower among prospective than historical patients (56.8% vs. 66.9%). Twice-weekly evaluations increased identification of mild ADEs, prompting higher suspension rates than weekly evaluations. While twice-weekly evaluations identified ADEs earlier, they did not reduce incidence of moderate or severe ADEs. Many dermatologic ADEs were moderately severe upon presentation (35.6%), were not reduced by use of antihistamines, occurred among adult patients of all ages, and occurred throughout treatment, rather than the first few weeks alone.

Conclusions

Intensive management improved completion and identified more ADEs, but did not reduce moderate or severe ADEs. Risk of dermatologic ADEs cannot be reduced by selecting younger adults or monitoring only during the first few weeks of treatment. Pill counts and phone-based encounters are reliable tools for treatment programming in rural Bolivia.     

Rural/urban Background,Depression and Suicidal Ideation in Chinese College Students: A Cross-Sectional Study

Objectives

The objective of this study was to examine, first, the relationship of having a rural vs. urban background with suicidal ideation in Chinese college students, and second, whether a potential relationship was mediated by depression.

Methods

A survey was conducted among 1,145 undergraduate students at a university in China. Suicidal ideation and depressive symptoms were measured by the revised Hopkins’ Symptom checklist (SCL-90-R). Associations between rural vs. urban background, depression and suicidal ideation were estimated by multivariable linear regression-based β coefficients, logistic regression-based odds ratios (ORs), and corresponding 95% confidence intervals (CIs). The magnitude of indirect effect and bias-corrected 95% CIs were obtained through bootstrap techniques.

Results

Rural background was positively associated with depression, which was in turn associated with suicidal ideation. The OR for rural status and suicidal ideation equaled 2.15 (95% CI = 1.36–3.41). This OR was slightly, though significantly (p<0.05) attenuated by additional adjustment for depressive symptoms (OR = 1.99, 95% CI = 1.15–3.44).

Conclusion

Having a rural background is a determinant of suicidal ideation in Chinese college students. Depression may only marginally mediate this association.     

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.     

Mortality Trends Observed in Population-Based Surveillance of an Urban Slum Settlement,Kibera, Kenya, 2007–2010

Background

We used population based infectious disease surveillance to characterize mortality rates in residents of an urban slum in Kenya.

Methods

We analyzed biweekly household visit data collected two weeks before death for 749 cases who died during January 1, 2007 to December 31, 2010. We also selected controls matched by age, gender and having a biweekly household visit within two weeks before death of the corresponding case and compared the symptoms reported.

Results

The overall mortality rate was 6.3 per 1,000 person years of observation (PYO) (females: 5.7; males: 6.8). Infant mortality rate was 50.2 per 1000 PYOs, and it was 15.1 per 1,000 PYOs for children <5 years old. Poisson regression indicates a significant decrease over time in overall mortality from (6.0 in 2007 to 4.0 in 2010 per 1000 PYOs; p<0.05) in persons ≥5 years old. This decrease was predominant in females (7.8 to 5.7 per 1000 PYOs; p<0.05). Two weeks before death, significantly higher prevalence for cough (OR = 4.7 [95% CI: 3.7–5.9]), fever (OR = 8.1 [95% CI: 6.1–10.7]), and diarrhea (OR = 9.1 [95% CI: 6.4–13.2]) were reported among participants who died (cases) when compared to participants who did not die (controls). Diarrhea followed by fever were independently associated with deaths (OR = 14.4 [95% CI: 7.1–29.2]), and (OR = 11.4 [95% CI: 6.7–19.4]) respectively.

Conclusions

Despite accessible health care, mortality rates are high among people living in this urban slum; infectious disease syndromes appear to be linked to a substantial proportion of deaths. Rapid urbanization poses an increasing challenge in national efforts to improve health outcomes, including reducing childhood mortality rates. Targeting impoverished people in urban slums with effective interventions such as water and sanitation interventions are needed to achieve national objectives for health.     

Climate Variability,Weather and Enteric Disease Incidence in New Zealand: Time Series Analysis

Background

Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases.

Objectives

To examine the associations between regional climate variability and enteric disease incidence in New Zealand.

Methods

Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models.

Results

No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  −0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher.

Conclusions

Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.     

Assessment of a Syndromic Surveillance System Based on Morbidity Data: Results from the Oscour? Network during a Heat Wave

Background

Syndromic surveillance systems have been developed in recent years and are now increasingly used by stakeholders to quickly answer questions and make important decisions. It is therefore essential to evaluate the quality and utility of such systems. This study was designed to assess a syndromic surveillance system based on emergency departments'' (ED) morbidity rates related to the health effects of heat waves. This study uses data collected during the 2006 heat wave in France.

Methods

Data recorded from 15 EDs in the Ile-de-France (Paris and surrounding area) from June to August, 2006, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected included diagnosis (ICD10), outcome, and age. Several aspects of the system have been evaluated (data quality, cost, flexibility, stability, and performance). Periods of heat wave are considered the most suitable time to evaluate the system.

Results

Data quality did not vary significantly during the period. Age, gender and outcome were completed in a comprehensive manner. Diagnoses were missing or uninformative for 37.5% of patients. Stability was recorded as being 99.49% for the period overall. The average cost per day over the study period was estimated to be €287. Diagnoses of hyperthermia, malaise, dehydration, hyponatremia were correlated with increased temperatures. Malaise was most sensitive in younger and elderly adults but also the less specific. However, overall syndrome groups were more sensitive with comparable specificity than individual diagnoses.

Conclusion

This system satisfactorily detected the health impact of hot days (observed values were higher than expected on more than 90% of days on which a heat alert was issued). Our findings should reassure stakeholders about the reliability of health impact assessments during or following such an event. These evaluations are essential to establish the validity of the results of syndromic surveillance systems.     

Bloodstream Infection among Adults in Phnom Penh,Cambodia: Key Pathogens and Resistance Patterns

Background

Bloodstream infections (BSI) cause important morbidity and mortality worldwide. In Cambodia, no surveillance data on BSI are available so far.

Methods

From all adults presenting with SIRS at Sihanouk Hospital Centre of HOPE (July 2007–December 2010), 20 ml blood was cultured. Isolates were identified using standard microbiological techniques; antibiotic susceptibilities were assessed using disk diffusion and MicroScan®, with additional E-test, D-test and double disk test where applicable, according to CLSI guidelines.

Results

A total of 5714 samples from 4833 adult patients yielded 501 clinically significant organisms (8.8%) of which 445 available for further analysis. The patients’ median age was 45 years (range 15–99 y), 52.7% were women. HIV-infection and diabetes were present in 15.6% and 8.8% of patients respectively. The overall mortality was 22.5%. Key pathogens included Escherichia coli (n = 132; 29.7%), Salmonella spp. (n = 64; 14.4%), Burkholderia pseudomallei (n = 56; 12.6%) and Staphylococcus aureus (n = 53; 11.9%). Methicillin resistance was seen in 10/46 (21.7%) S. aureus; 4 of them were co-resistant to erythromycin, clindamycin, moxifloxacin and sulphamethoxazole-trimethoprim (SMX-TMP). We noted combined resistance to amoxicillin, SMX-TMP and ciprofloxacin in 81 E. coli isolates (62.3%); 62 isolates (47.7%) were confirmed as producers of extended spectrum beta-lactamase. Salmonella isolates displayed high rates of multidrug resistance (71.2%) with high rates of decreased ciprofloxacin susceptibility (90.0%) in Salmonella Typhi while carbapenem resistance was observed in 5.0% of 20 Acinetobacter sp. isolates.

Conclusions

BSI in Cambodian adults is mainly caused by difficult-to-treat pathogens. These data urge for microbiological capacity building, nationwide surveillance and solid interventions to contain antibiotic resistance.     

Elementary School-Based Influenza Vaccination: Evaluating Impact on Respiratory Illness Absenteeism and Laboratory-Confirmed Influenza

Background

Studies of influenza vaccine effectiveness in schools have assessed all-cause absenteeism rather than laboratory-confirmed influenza. We conducted an observational pilot study to identify absences due to respiratory illness and laboratory-confirmed influenza in schools with and without school-based vaccination.

Methods

A local public health agency initiated school-based influenza vaccination in two Wisconsin elementary schools during October 2010 (exposed schools); two nearby schools served as a comparison group (non-exposed schools). Absences due to fever or cough illness were monitored for 12 weeks. During the 4 weeks of peak influenza activity, parents of absent children with fever/cough illness were contacted and offered influenza testing.

Results

Parental consent for sharing absenteeism data was obtained for 937 (57%) of 1,640 students. Fifty-two percent and 28%, respectively, of all students in exposed and non-exposed schools were vaccinated. Absences due to fever or cough illness were significantly lower in the exposed schools during seven of 12 surveillance weeks. Twenty-seven percent of students at exposed schools and 39% at unexposed schools had one or more days of absence due to fever/cough illness (p<0.0001). There was no significant difference in the proportion of students absent for other reasons (p = 0.23). During the 4 week period of influenza testing, respiratory samples were obtained for 68 (42%) of 163 episodes of absence due to fever or cough illness. Influenza was detected in 6 students; 3 attended exposed schools.

Conclusions

Detection of laboratory-confirmed influenza in schools was challenging due to multiple consent requirements, difficulty obtaining samples from absent children, and a mild influenza season. School-based influenza vaccination was associated with reduced absenteeism due to fever or cough illness, but not absenteeism for other reasons. Although nonspecific, absence due to fever or cough illness may be a useful surrogate endpoint in school-based studies if identification of laboratory confirmed influenza is not feasible.     

Infectious Complications in Head and Neck Cancer Patients Treated with Cetuximab: Propensity Score and Instrumental Variable Analysis

Background

To compare the infection rates between cetuximab-treated patients with head and neck cancers (HNC) and untreated patients.

Methodology

A national cohort of 1083 HNC patients identified in 2010 from the Taiwan National Health Insurance Research Database was established. After patients were followed for one year, propensity score analysis and instrumental variable analysis were performed to assess the association between cetuximab therapy and the infection rates.

Results

HNC patients receiving cetuximab (n = 158) were older, had lower SES, and resided more frequently in rural areas as compared to those without cetuximab therapy. 125 patients, 32 (20.3%) in the group using cetuximab and 93 (10.1%) in the group not using it presented infections. The propensity score analysis revealed a 2.3-fold (adjusted odds ratio [OR] = 2.27; 95% CI, 1.46–3.54; P = 0.001) increased risk for infection in HNC patients treated with cetuximab. However, using IVA, the average treatment effect of cetuximab was not statistically associated with increased risk of infection (OR, 0.87; 95% CI, 0.61–1.14).

Conclusions

Cetuximab therapy was not statistically associated with infection rate in HNC patients. However, older HNC patients using cetuximab may incur up to 33% infection rate during one year. Particular attention should be given to older HNC patients treated with cetuximab.