Factors influencing the performance of voluntary farmer disease reporting in passive surveillance systems: A scoping review

Abstract Background Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care. Methods We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria. Results Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations’ financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years. Conclusions Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.

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Measuring perceived adequacy of staffing to incorporate nurses’ judgement into hospital capacity management: a scoping review

BMJ Open ◽

10.1136/bmjopen-2020-045245 ◽

2021 ◽

Vol 11 (4) ◽

pp. e045245

Author(s):

Carmen J E M van der Mark ◽

Hester Vermeulen ◽

Paul H J Hendriks ◽

Catharina J van Oostveen

Keyword(s):

Psychometric Properties ◽

Scoping Review ◽

Care Delivery ◽

Hospital Setting ◽

Workforce Planning ◽

Nurse Staffing ◽

Measurement Instruments ◽

Health Measurement ◽

Factors Influencing

BackgroundMatching demand and supply in nursing work continues to generate debate. Current approaches focus on objective measures, such as nurses per occupied bed or patient classification. However, staff numbers do not tell the whole staffing story. The subjective measure of nurses’ perceived adequacy of staffing (PAS) has the potential to enhance nurse staffing methods in a way that goes beyond traditional workload measurement or workforce planning methods.ObjectivesTo detect outcomes associated with nurses’ PAS and the factors that influence PAS and to review the psychometric properties of instruments used to measure PAS in a hospital setting.Design and methodsA scoping review was performed to identify outcomes associated with PAS, factors influencing PAS and instruments measuring PAS. A search of PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Business Source Complete and Embase databases identified 2609 potentially relevant articles. Data were independently extracted, analysed and synthesised. The quality of studies describing influencing factors or outcomes of PAS and psychometric properties of instruments measuring PAS were assessed following the National Institute for Health and Care Excellence quality appraisal checklist and the COnsensus-based Standards for the selection of health Measurement INstruments guidelines.ResultsSixty-three studies were included, describing 60 outcomes of PAS, 79 factors influencing PAS and 21 instruments measuring PAS. In general, positive PAS was related to positive outcomes for the patient, nurse and organisation, supporting the relevance of PAS as a staffing measure. We identified a variety of factors that influence PAS, including demand for care, nurse supply and organisation of care delivery. Associations between these factors and PAS were inconsistent. The quality of studies investigating the development and evaluation of instruments measuring PAS was moderate.ConclusionsMeasuring the PAS may enhance nurse staffing methods in a hospital setting. Further work is needed to refine and psychometrically evaluate instruments for measuring PAS.

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Is over-reporting a problem in mandatory communicable disease reporting? The taiwanese experience on Enterovirus 71

The Journal of Infection in Developing Countries ◽

10.3855/jidc.4623 ◽

2014 ◽

Vol 8 (10) ◽

pp. 1294-1300

Author(s):

Tseng Chu-Chun ◽

Yang Che-Ming

Keyword(s):

Communicable Disease ◽

Enterovirus 71 ◽

Surveillance Systems ◽

Accuracy Rate ◽

Cross Sectional ◽

Systems Methodology ◽

Disease Reporting ◽

Enteroviral Infection ◽

District Hospitals ◽

The Government

Introduction: In Taiwan, severe enteroviral infections must be reported to the government within 24 hours to ensure that severe enterovirus 71 (EV71) infections can be detected early. The objective of this research was to ascertain whether over-reporting is a problem in mandatory disease-reporting systems. Methodology: A multiyear cross-sectional study methodology was applied based on secondary data analyses. Data from the national notifiable communicable disease surveillance system of Taiwan Centers for Disease Control were analyzed to assess the trends and factors influencing reporting accuracy. Results: From July 1999 to December 2008, 2,611 cases of severe enteroviral infection were reported in Taiwan. Among these cases, 1,516 were confirmed to be EV71 cases, and the remaining 1,095 were confirmed to be non-EV71 infections. The overall accuracy rate was 58%. The accuracy rate was 60%–70% higher during epidemics (2000–2002, 2005, and 2008) and high seasons than it was in other seasons. The accuracy rate was highest among medical centers and lowest among district hospitals. Conclusions: The results indicated that reports are more accurate during high seasons and peak years than during other periods. This might be attributable to the adequate level of specific educational programs for professionals when more cases occur, which could facilitate identification. Based on experiences in Taiwan, optimal training can ensure that surveillance systems are not inundated by false-positive reports.

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