scholarly journals Response to: “letter to the editor regarding the article “the global distribution of acute unintentional pesticide poisoning: estimations based on a systematic review”” by Dunn et al. 2021 in BMC public health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wolfgang Boedeker ◽  
Meriel Watts ◽  
Peter Clausing ◽  
Emily Marquez

AbstractIn a correspondence to BMC Public Health, Dunn et al. (Dunn SE, Reed J and Neumann C. BMC Public Health (n.d)) respond to our review on the occurrence of unintentional, acute pesticide poisoning (UAPP). Based on a systematic review and further data sources we estimated that about 385 million cases of UAPP occur annually world-wide including around 11,000 fatalities (Boedeker W. et al. BMC Public Health:1875, 2020).

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wolfgang Boedeker ◽  
Meriel Watts ◽  
Peter Clausing ◽  
Emily Marquez

Abstract Background Human poisoning by pesticides has long been seen as a severe public health problem. As early as 1990, a task force of the World Health Organization (WHO) estimated that about one million unintentional pesticide poisonings occur annually, leading to approximately 20,000 deaths. Thirty years on there is no up-to-date picture of global pesticide poisoning despite an increase in global pesticide use. Our aim was to systematically review the prevalence of unintentional, acute pesticide poisoning (UAPP), and to estimate the annual global number of UAPP. Methods We carried out a systematic review of the scientific literature published between 2006 and 2018, supplemented by mortality data from WHO. We extracted data from 157 publications and the WHO cause-of-death database, then performed country-wise synopses, and arrived at annual numbers of national UAPP. World-wide UAPP was estimated based on national figures and population data for regions defined by the Food and Agriculture Organization (FAO). Results In total 141 countries were covered, including 58 by the 157 articles and an additional 83 by data from the WHO Mortality Database. Approximately 740,000 annual cases of UAPP were reported by the extracted publications resulting from 7446 fatalities and 733,921 non-fatal cases. On this basis, we estimate that about 385 million cases of UAPP occur annually world-wide including around 11,000 fatalities. Based on a worldwide farming population of approximately 860 million this means that about 44% of farmers are poisoned by pesticides every year. The greatest estimated number of UAPP cases is in southern Asia, followed by south-eastern Asia and east Africa with regards to non-fatal UAPP. Conclusions Our study updates outdated figures on world-wide UAPP. Along with other estimates, robust evidence is presented that acute pesticide poisoning is an ongoing major global public health challenge. There is a need to recognize the high burden of non-fatal UAPP, particularly on farmers and farmworkers, and that the current focus solely on fatalities hampers international efforts in risk assessment and prevention of poisoning. Implementation of the international recommendations to phase out highly hazardous pesticides by the FAO Council could significantly reduce the burden of UAPP.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
S. Eliza Dunn ◽  
Jennifer E. Reed ◽  
Christoph Neumann

AbstractWe read with interest the article entitled “The global distribution of acute unintentional pesticide poisoning: estimations based on a systematic review”. We wholeheartedly agree that it is important to evaluate the extent of this issue. We would like to understand the numbers provided in this article, which appear to overestimate the global burden of pesticide poisonings. We also feel that addressing the benefits of these chemistries is important for a complete evaluation.


BMJ ◽  
2020 ◽  
pp. m4143
Author(s):  
Nathan Ford ◽  
Grania Brigden ◽  
Tom Ellman ◽  
Edward J Mills

Abstract Objective To identify any medical or public health rationale for claims that the time to act is now. Design Pseudo-systematic review. Data sources PubMed. Study selection Studies that included the claim “time is now” in the title, with or without exclamation marks. No language or date restriction was applied. Results 512 articles were included for review. No relationship was identified between time to act and disease burden, severity, or specialty. Claims that the time to act was Christmas were almost entirely without basis. A clustering of claims that it is time to act in the first quarter of the year suggested a possible association with New Year’s resolutions. Conclusions Now is as good a time as any.


2021 ◽  
Author(s):  
Carina Nina Vorisek ◽  
Moritz Lehne ◽  
Sophie Anne Ines Klopfenstein ◽  
Alexander Bartschke ◽  
Thomas Haese ◽  
...  

BACKGROUND The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important. FHIR provides solutions by offering resource domains such as “Public Health & Research” and “Evidence-Based Medicine” while using already established web technologies. Therefore, FHIR could help to standardize data across different data sources and improve interoperability in health research. OBJECTIVE The aim of our study was to provide a systematic review of existing literature and determine the current state of FHIR implementations in health research and possible future directions. METHODS We searched PubMed/Medline, EMBASE, Web of Science, IEEE Xplore and the Cochrane Library databases for studies published from 2010 to 2021. Studies investigating the use of FHIR in health research were included. Articles published before 2010, abstracts, reviews, editorials and expert opinions were excluded. We followed the PRISMA guidelines and registered this study with PROSPERO, CRD42021235393. Data synthesis was done in tables and figures. RESULTS We identified a total of 674 studies, of which 28 studies were eligible for inclusion. Most studies covered the domain of clinical research (22/28) while the remaining studies focused on public health/ epidemiology (3/28) or did not specify their research domain (3/28). Studies used FHIR for data capture (11/28), standardization of data (7/28), analysis (4/28), recruitment (4/28) and consent management (2/28). Most studies had a generic approach (15/28) and nine of 13 studies focusing on specific medical specialties (infectious disease, genomics, oncology, environmental health, imaging, pulmonary hypertension) reported their solutions to be conferrable to other use cases. Half of the studies reported using additional data models or terminologies: SNOMED CT (8/14), LOINC (8/14), ICD-10 (6/14), OMOP CDM (3/14) and others (9/14). Only one study used a FHIR resource from the domain “Public Health & Research”. Limitations using FHIR included the possible change in the content of FHIR resources, safety and legal matters and the need for a FHIR server. CONCLUSIONS Our review found that FHIR can be implemented in health research and that the areas of application are broad and generalizable in most use cases. Implementation of international terminologies was common and other standards such as OMOP CDM could be used complementary with FHIR. Limitations such as change of FHIR content, lack of FHIR implementation, safety and legal matters need to be addressed in future releases to expand the use of FHIR and therefore interoperability in health research.


2019 ◽  
Author(s):  
P-Y Kobres ◽  
JP Chretien ◽  
MA Johansson ◽  
J Morgan ◽  
P-Y Whung ◽  
...  

AbstractINTRODUCTIONEpidemic forecasting and prediction tools have the potential to provide actionable information in the midst of emerging epidemics. While numerous predictive studies were published during the 2016-2017 Zika Virus (ZIKV) pandemic, it remains unknown how timely, reproducible and actionable the information produced by these studies was.METHODSTo improve the functional use of mathematical modeling in support of future infectious disease outbreaks, we conducted a systematic review of all ZIKV prediction studies published during the recent ZIKV pandemic using the PRISMA guidelines. Using MEDLINE, EMBASE and grey literature review, we identified studies that forecasted, predicted or simulated ecological or epidemiological phenomenon related to the Zika pandemic that were published as of March 01, 2017. Eligible studies underwent evaluation of objectives, data sources, methods, timeliness, reproducibility, accessibility and clarity by independent reviewers.RESULTS2034 studies were identified, of which n = 73 met eligibility criteria. Spatial spread, R0 (basic reproductive number) and epidemic dynamics were most commonly predicted, with few studies predicting Guillain-Barré Syndrome burden (4%), sexual transmission risk (4%) and intervention impact (4%). Most studies specifically examined populations in the Americas (52%), with few African-specific studies (4%). Case count (67%), vector (41%) and demographic data (37%) were the most common data sources. Real-time internet data and pathogen genomic information were used in 7% and 0% of studies, respectively, and social science and behavioral data were typically absent in modeling efforts. Deterministic models were favored over stochastic approaches. Forty percent of studies made model data entirely available, 29% provided all relevant model code, 43% presented uncertainty in all predictions and 54% provided sufficient methodological detail allowing complete reproducibility. Fifty-one percent of predictions were published after the epidemic peak in the Americas. While the use of preprints improved the accessibility of ZIKV predictions by a median 119 days sooner than journal publication dates, they were used in only 30% of studies.CONCLUSIONSMany ZIKV predictions were published during the 2016-2017 pandemic. The accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. To enhance the utility of analytical tools for outbreak response, it is essential to improve the sharing of model data, code, and preprints for future outbreaks, epidemics and pandemics.Author summaryResearchers published many studies which sought to predict and forecast important features of Zika virus (ZIKV) infections and their spread during the 2016-2017 ZIKV pandemic. We conducted a comprehensive review of such ZIKV prediction studies and evaluated their aims, the data sources they used, which methods were used, how timely they were published, and whether they provided sufficient information to be used or reproduced by others. Of the 73 studies evaluated, we found that the accessibility, reproducibility, timeliness, and incorporation of uncertainty in these published predictions varied and indicates that there is substantial room for improvement. We identified that the release of study findings before formal journal publication (‘pre-prints’) increased the timeliness of Zika prediction studies, but note they were infrequently used during this public health emergency. Addressing these areas can improve our understanding of Zika and other outbreaks and ensure that forecasts can inform preparedness and response to future outbreaks, epidemics and pandemics.


BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e037405
Author(s):  
Daniel Dedman ◽  
Melissa Cabecinha ◽  
Rachael Williams ◽  
Stephen J W Evans ◽  
Krishnan Bhaskaran ◽  
...  

ObjectiveTo identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources.DesignA systematic review of published studies.Data sourcesPubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening.Study selectionObservational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases.Results6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies.ConclusionsComparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.


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