The hidden costs: Identification of indirect costs associated with acute gastrointestinal illness in an Inuit community

Background: Acute gastrointestinal illness (AGI) incidence and per-capita healthcare expenditures are higher in some Inuit communities as compared to elsewhere in Canada. Consequently, there is a demand for strategies that will reduce the individual-level costs of AGI; this will require a comprehensive understanding of the economic costs of AGI. However, given Inuit communities’ unique cultural, economic, and geographic contexts, there is a knowledge gap regarding the context-specific indirect costs of AGI borne by Inuit community members. This study aimed to identify the major indirect costs of AGI, and explore factors associated with these indirect costs, in the Inuit community of Rigolet, Canada, in order to develop a case-based context-specific study framework that can be used to evaluate these costs. Methods: A mixed methods study design and community-based methods were used. Qualitative in-depth, group, and case interviews were analyzed using thematic analysis to identify and describe indirect costs of AGI specific to Rigolet. Data from two quantitative cross-sectional retrospective surveys were analyzed using univariable regression models to examine potential associations between predictor variables and the indirect costs. Results/Significance: The most notable indirect costs of AGI that should be incorporated into cost-of-illness evaluations were the tangible costs related to missing paid employment and subsistence activities, as well as the intangible costs associated with missing community and cultural events. Seasonal cost variations should also be considered. This study was intended to inform cost-of-illness studies conducted in Rigolet and other similar research settings. These results contribute to a better understanding of the economic impacts of AGI on Rigolet residents, which could be used to help identify priority areas and resource allocation for public health policies and programs

Association of Over-The-Counter Pharmaceutical Sales with Influenza-Like-Illnesses to Patient Volume in an Urgent Care Setting

We studied the association between OTC pharmaceutical sales and volume of patients with influenza-like-illnesses (ILI) at an urgent care center over one year. OTC pharmaceutical sales explain 36% of the variance in the patient volume, and each standard deviation increase is associated with 4.7 more patient visits to the urgent care center (p<0.0001). Cross-correlation function analysis demonstrated that OTC pharmaceutical sales are significantly associated with patient volume during non-flu season (p<0.0001), but only the sales of cough and cold (p<0.0001) and thermometer (p<0.0001) categories were significant during flu season with a lag of two and one days, respectively. Our study is the first study to demonstrate and measure the relationship between OTC pharmaceutical sales and urgent care center patient volume, and presents strong evidence that OTC sales predict urgent care center patient volume year round. © 2013 Liu et al

Healthcare use for acute gastrointestinal illness in two Inuit communities: Rigolet and Iqaluit, Canada

Background. The incidence of self-reported acute gastrointestinal illness (AGI) in Rigolet, Nunatsiavut, and Iqaluit, Nunavut, is higher than reported elsewhere in Canada; as such, understanding AGI-related healthcare use is important for healthcare provision, public health practice and surveillance of AGI. Objectives: This study described symptoms, severity and duration of self-reported AGI in the general population and examined the incidence and factors associated with healthcare utilization for AGI in these 2 Inuit communities. Design: Cross-sectional survey data were analysed using multivariable exact logistic regression to examine factors associated with individuals’ self-reported healthcare and over-the-counter (OTC) medication utilization related to AGI symptoms. Results: In Rigolet, few AGI cases used healthcare services [4.8% (95% CI=1.5-14.4%)]; in Iqaluit, some cases used healthcare services [16.9% (95% CI=11.2-24.7%)]. Missing traditional activities due to AGI (OR=3.8; 95% CI=1.18-12.4) and taking OTC medication for AGI symptoms (OR=3.8; 95% CI=1.2-15.1) were associated with increased odds of using healthcare services in Iqaluit. In both communities, AGI severity and secondary symptoms (extreme tiredness, headache, muscle pains, chills) were significantly associated with increased odds of taking OTC medication. Conclusions: While rates of self-reported AGI were higher in Inuit communities compared to non-Inuit communities in Canada, there were lower rates of AGI-related healthcare use in Inuit communities compared to other regions in Canada. As such, the rates of healthcare use for a given disease can differ between Inuit and non-Inuit communities, and caution should be exercised in making comparisons between Inuit and non-Inuit health outcomes based solely on clinic records and healthcare use

Water quality and health in northern Canada: stored drinking water and acute gastrointestinal illness in Labrador Inuit

One of the highest self-reported incidence rates of acute gastrointestinal illness (AGI) in the global peer-reviewed literature occurs in Inuit communities in the Canadian Arctic. This high incidence of illness could be due, in part, to the consumption of contaminated water, as many northern communities face challenges related to the quality of municipal drinking water. Furthermore, many Inuit store drinking water in containers in the home, which could increase the risk of contamination between source and point-of-use (i.e., water recontamination during storage). To examine this risk, this research characterized drinking water collection and storage practices, identified potential risk factors for water contamination between source and point-of-use, and examined possible associations between drinking water contamination and self-reported AGI in the Inuit community of Rigolet, Canada. The study included a cross-sectional census survey that captured data on types of drinking water used, household practices related to drinking water (e.g., how it was collected and stored), physical characteristics of water storage containers, and self-reported AGI. Additionally, water samples were collected from all identified drinking water containers in homes and analyzed for presence of Escherichia coli and total coliforms. Despite municipally treated tap water being available in all homes, 77.6% of households had alternative sources of drinking water stored in containers, and of these containers, 25.2% tested positive for total coliforms. The use of transfer devices and water dippers (i.e., smaller bowls or measuring cups) for the collection and retrieval of water from containers were both significantly associated with increased odds of total coliform presence in stored water (ORtransfer device = 3.4, 95% CI 1.2–11.7; ORdipper = 13.4, 95% CI 3.8–47.1). Twenty-eight-day period prevalence of self-reported AGI during the month before the survey was 17.2% (95% CI 13.0–22.5), which yielded an annual incidence rate of 2.4 cases per person per year (95% CI 1.8–3.1); no water-related risk factors were significantly associated with AGI. Considering the high prevalence of, and risk factors associated with, indicator bacteria in drinking water stored in containers, potential exposure to waterborne pathogens may be minimized through interventions at the household level

Understanding Weather and Hospital Admissions Patterns to Inform Climate Change Adaptation Strategies in the Healthcare Sector in Uganda

Background: Season and weather are associated with many health outcomes, which can influence hospital admission rates. We examined associations between hospital admissions (all diagnoses) and local meteorological parameters in Southwestern Uganda, with the aim of supporting hospital planning and preparedness in the context of climate change. Methods: Hospital admissions data and meteorological data were collected from Bwindi Community Hospital and a satellite database of weather conditions, respectively (2011 to 2014). Descriptive statistics were used to describe admission patterns. A mixed-effects Poisson regression model was fitted to investigate associations between hospital admissions and season, precipitation, and temperature. Results: Admission counts were highest for acute respiratory infections, malaria, and acute gastrointestinal illness, which are climate-sensitive diseases. Hospital admissions were 1.16 (95% CI: 1.04, 1.31; p = 0.008) times higher during extreme high temperatures (i.e., >95th percentile) on the day of admission. Hospital admissions association with season depended on year; admissions were higher in the dry season than the rainy season every year, except for 2014. Discussion: Effective adaptation strategy characteristics include being low-cost and quick and practical to implement at local scales. Herein, we illustrate how analyzing hospital data alongside meteorological parameters may inform climate-health planning in low-resource contexts

Summary of data reported to CDC's national automated biosurveillance system, 2008

<p>Abstract</p> <p>Background</p> <p>BioSense is the US national automated biosurveillance system. Data regarding chief complaints and diagnoses are automatically pre-processed into 11 broader syndromes (e.g., respiratory) and 78 narrower sub-syndromes (e.g., asthma). The objectives of this report are to present the types of illness and injury that can be studied using these data and the frequency of visits for the syndromes and sub-syndromes in the various data types; this information will facilitate use of the system and comparison with other systems.</p> <p>Methods</p> <p>For each major data source, we summarized information on the facilities, timeliness, patient demographics, and rates of visits for each syndrome and sub-syndrome.</p> <p>Results</p> <p>In 2008, the primary data sources were the 333 US Department of Defense, 770 US Veterans Affairs, and 532 civilian hospital emergency department facilities. Median times from patient visit to record receipt at CDC were 2.2 days, 2.0 days, and 4 hours for these sources respectively. Among sub-syndromes, we summarize mean 2008 visit rates in 45 infectious disease categories, 11 injury categories, 7 chronic disease categories, and 15 other categories.</p> <p>Conclusions</p> <p>We present a systematic summary of data that is automatically available to public health departments for monitoring and responding to emergencies.</p

Expression analysis of carbohydrate antigens in ductal carcinoma in situ of the breast by lectin histochemistry

<p>Abstract</p> <p>Background</p> <p>The number of breast cancer patients diagnosed with ductal carcinoma <it>in situ </it>(DCIS) continues to grow. Laboratory and clinical data indicate that DCIS can progress to invasive disease. Carbohydrate-mediated cell-cell adhesion and tumor-stroma interaction play crucial roles in tumorigenesis and tumor aggressive behavior. Breast carcinogenesis may reflect quantitative as well as qualitative changes in oligosaccharide expression, which may provide a useful tool for early detection of breast cancer. Because tumor-associated carbohydrate antigens (TACA) are implicated in tumor invasion and metastasis, the purpose of this study was to assess the expression of selected TACA by lectin histochemistry on DCIS specimens from the archival breast cancer tissue array bank of the University of Arkansas for Medical Sciences.</p> <p>Methods</p> <p>For detection of TACA expression, specimens were stained with <it>Griffonia simplicifolia </it>lectin-I (GS-I) and <it>Vicia vilosa </it>agglutinin (VVA). We studied associations of lectin reactivity with established prognostic factors, such as tumor size, tumor nuclear grade, and expression of Her-2/neu, p53 mutant and estrogen and progesterone receptors.</p> <p>Results</p> <p>We observed that both lectins showed significant associations with nuclear grade of DCIS. DCIS specimens with nuclear grades II and III showed significantly more intense reactivity than DCIS cases with nuclear grade I to GS-1 (Mean-score chi-square = 17.60, DF = 2; <it>P </it>= 0.0002) and VVA (Mean-score chi-square = 15.72, DF = 2; <it>P </it>= 0.0004).</p> <p>Conclusion</p> <p>The results suggest that the expression of VVA- and GS-I-reactive carbohydrate antigens may contribute to forming higher grade DCIS and increase the recurrence risk.</p

Using Ontario's "Telehealth" health telephone helpline as an early-warning system: a study protocol

BACKGROUND: The science of syndromic surveillance is still very much in its infancy. While a number of syndromic surveillance systems are being evaluated in the US, very few have had success thus far in predicting an infectious disease event. Furthermore, to date, the majority of syndromic surveillance systems have been based primarily in emergency department settings, with varying levels of enhancement from other data sources. While research has been done on the value of telephone helplines on health care use and patient satisfaction, very few projects have looked at using a telephone helpline as a source of data for syndromic surveillance, and none have been attempted in Canada. The notable exception to this statement has been in the UK where research using the national NHS Direct system as a syndromic surveillance tool has been conducted. METHODS/DESIGN: The purpose of our proposed study is to evaluate the effectiveness of Ontario's telephone nursing helpline system as a real-time syndromic surveillance system, and how its implementation, if successful, would have an impact on outbreak event detection in Ontario. Using data collected retrospectively, all "reasons for call" and assigned algorithms will be linked to a syndrome category. Using different analytic methods, normal thresholds for the different syndromes will be ascertained. This will allow for the evaluation of the system's sensitivity, specificity and positive predictive value. The next step will include the prospective monitoring of syndromic activity, both temporally and spatially. DISCUSSION: As this is a study protocol, there are currently no results to report. However, this study has been granted ethical approval, and is now being implemented. It is our hope that this syndromic surveillance system will display high sensitivity and specificity in detecting true outbreaks within Ontario, before they are detected by conventional surveillance systems. Future results will be published in peer-reviewed journals so as to contribute to the growing body of evidence on syndromic surveillance, while also providing an non US-centric perspective

Rapid detection of pandemic influenza in the presence of seasonal influenza

Background: Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland. Methods: We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data. Results: We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland. Conclusions: While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical