Dataset Information

Comparing methods of performing geographically targeted rural health surveillance.

ABSTRACT: Background: Worsening socioeconomic conditions in rural America have been fueling increases in chronic disease and poor health. The goal of this study was to identify cost-effective methods of deploying geographically targeted health surveys in rural areas, which often have limited resources. These health surveys were administered in New York's rural Sullivan County, which has some of the poorest health outcomes in the entire state.

Methods: Comparisons were made for response rates, estimated costs, respondent demographics, and prevalence estimates of a brief health survey delivered by mail and phone using address-based sampling, and in-person using convenience sampling at a sub-county level in New York's rural Sullivan County during 2017.

Results: Overall response rates were 27.0% by mail, 8.2% by phone, and 71.4% for convenience in-person surveys. Costs to perform phone surveys were substantially higher than mailed or convenience in-person surveys. All modalities had lower proportions of Hispanic respondents compared to Census estimates. Unadjusted and age-adjusted prevalence estimates were similar between mailed and in-person surveys, but not for phone surveys.

Conclusions: These findings are consistent with declining response rates of phone surveys, which obtained an inadequate sample of rural residents. Though in-person surveys had higher response rates, convenience sampling failed to obtain a geographically distributed sample of rural residents. Of modalities tested, mailed surveys provided the best opportunity to perform geographically targeted rural health surveillance.

SUBMITTER: Lee DC

PROVIDER: S-EPMC7686693 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Comparing methods of performing geographically targeted rural health surveillance.

Lee David C DC McGraw Nancy A NA Doran Kelly M KM Mengotto Amanda K AK Wiener Sara L SL Vinson Andrew J AJ Thorpe Lorna E LE

Emerging themes in epidemiology 20201123 1

<h4>Background</h4>Worsening socioeconomic conditions in rural America have been fueling increases in chronic disease and poor health. The goal of this study was to identify cost-effective methods of deploying geographically targeted health surveys in rural areas, which often have limited resources. These health surveys were administered in New York's rural Sullivan County, which has some of the poorest health outcomes in the entire state.<h4>Methods</h4>Comparisons were made for response rates, ...[more]

PMID: 33292290

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Project description:BackgroundTimely tracking of health outcomes is difficult in low- and middle-income countries without comprehensive vital registration systems. Community health workers (CHWs) are increasingly collecting vital events data while delivering routine care in low-resource settings. It is necessary, however, to assess whether routine programmatic data collected by CHWs are sufficiently reliable for timely monitoring and evaluation of health interventions. To study this, we assessed the consistency of vital events data recorded by CHWs using two methodologies-routine data collected while delivering an integrated maternal and child health intervention, and data from a birth history census approach at the same site in rural Nepal.MethodsWe linked individual records from routine programmatic data from June 2017 to May 2018 with those from census data, both collected by CHWs at the same site using a mobile platform. We categorized each vital event over a one-year period as 'recorded by both methods,' 'census alone,' or 'programmatic alone.' We further assessed whether vital events data recorded by both methods were classified consistently.ResultsFrom June 2017 to May 2018, we identified a total of 713 unique births collectively from the census (birth history) and programmatic maternal 'post-delivery' data. Three-fourths of these births (n = 526) were identified by both. There was high consistency in birth location classification among the 526 births identified by both methods. Upon including additional programmatic 'child registry' data, we identified 746 total births, of which 572 births were identified by both census and programmatic methods. Programmatic data (maternal 'post-delivery' and 'child registry' combined) captured more births than census data (723 vs. 595). Both methods consistently classified most infants as 'living,' while infant deaths and stillbirths were largely classified inconsistently or recorded by only one method. Programmatic data identified five infant deaths and five stillbirths not recorded in census data.ConclusionsOur findings suggest that data collected by CHWs from routinely tracking pregnancies, births, and deaths are promising for timely program monitoring and evaluation. Despite some limitations, programmatic data may be more sensitive in detecting vital events than cross-sectional census surveys asking women to recall these events.

Project description:Traditional methods of monitoring foodborne illness are associated with problems of untimeliness and underreporting. In recent years, alternative data sources such as social media data have been used to monitor the incidence of disease in the population (infodemiology and infoveillance). These data sources prove timelier than traditional general practitioner data, they can help to fill the gaps in the reporting process, and they often include additional metadata that is useful for supplementary research.The aim of the study was to identify and formally analyze research papers using consumer-generated data, such as social media data or restaurant reviews, to quantify a disease or public health ailment. Studies of this nature are scarce within the food safety domain, therefore identification and understanding of transferrable methods in other health-related fields are of particular interest.Structured scoping methods were used to identify and analyze primary research papers using consumer-generated data for disease or public health surveillance. The title, abstract, and keyword fields of 5 databases were searched using predetermined search terms. A total of 5239 papers matched the search criteria, of which 145 were taken to full-text review-62 papers were deemed relevant and were subjected to data characterization and thematic analysis.The majority of studies (40/62, 65%) focused on the surveillance of influenza-like illness. Only 10 studies (16%) used consumer-generated data to monitor outbreaks of foodborne illness. Twitter data (58/62, 94%) and Yelp reviews (3/62, 5%) were the most commonly used data sources. Studies reporting high correlations against baseline statistics used advanced statistical and computational approaches to calculate the incidence of disease. These include classification and regression approaches, clustering approaches, and lexicon-based approaches. Although they are computationally intensive due to the requirement of training data, studies using classification approaches reported the best performance.By analyzing studies in digital epidemiology, computer science, and public health, this paper has identified and analyzed methods of disease monitoring that can be transferred to foodborne disease surveillance. These methods fall into 4 main categories: basic approach, classification and regression, clustering approaches, and lexicon-based approaches. Although studies using a basic approach to calculate disease incidence generally report good performance against baseline measures, they are sensitive to chatter generated by media reports. More computationally advanced approaches are required to filter spurious messages and protect predictive systems against false alarms. Research using consumer-generated data for monitoring influenza-like illness is expansive; however, research regarding the use of restaurant reviews and social media data in the context of food safety is limited. Considering the advantages reported in this review, methods using consumer-generated data for foodborne disease surveillance warrant further investment.

Dataset Information

Comparing methods of performing geographically targeted rural health surveillance.

Publications

Comparing methods of performing geographically targeted rural health surveillance.

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