Who Manipulates Data During Pandemics? Evidence From Newcomb-Benford Law

Abstract The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb-Benford law (NBL) to gauge data accuracy. We run an OLS regression of developmental indicators (EIU index, GDP per capita, healthcare expenditures, and universal healthcare coverage index) on goodness-of-fit measures to the NBL. We find that democratic countries, countries with the higher gross domestic product (GDP) per capita, higher healthcare expenditures, and better universal healthcare coverage are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests, for a sub-sample of countries with regional data, and in relation to the previous swine flu (H1N1) 2009–2010 pandemic. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.JEL classification: F5, I10, I18, O1, O57, P52.

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Using the Newcomb–Benford law to study the association between a country’s COVID-19 reporting accuracy and its development

Scientific Reports ◽

10.1038/s41598-021-02367-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Vadim S. Balashov ◽

Yuxing Yan ◽

Xiaodi Zhu

Keyword(s):

Goodness Of Fit ◽

Developed Countries ◽

Cumulative Number ◽

Reporting Accuracy ◽

Universal Healthcare ◽

Developmental Indicators ◽

Developmental Index ◽

Reported Data ◽

The Relationship ◽

Benford Law

AbstractThe COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb–Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.

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Universal healthcare coverage for first episode of schizophrenia-spectrum disorders in Chile: analysis of the administrative database

European Archives of Psychiatry and Clinical Neuroscience ◽

10.1007/s00406-021-01254-y ◽

2021 ◽

Author(s):

Verónica Larach ◽

Luis F. Varela ◽

Guillermo Vergara ◽

Irma Rojas ◽

Viviana Hernández ◽

...

Keyword(s):

Administrative Database ◽

First Episode ◽

Schizophrenia Spectrum Disorders ◽

Universal Healthcare ◽

Schizophrenia Spectrum ◽

Healthcare Coverage ◽

Spectrum Disorders ◽

First Episode Of Schizophrenia ◽

Universal Healthcare Coverage

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Why does healthcare utilisation differ between socioeconomic groups in OECD countries with universal healthcare coverage? A protocol for a systematic review

BMJ Open ◽

10.1136/bmjopen-2021-054806 ◽

2021 ◽

Vol 11 (11) ◽

pp. e054806

Author(s):

Iris Meulman ◽

Ellen Uiters ◽

Johan Polder ◽

Niek Stadhouders

Keyword(s):

Systematic Review ◽

Healthcare Access ◽

Healthcare Utilisation ◽

Oecd Countries ◽

Primary Data ◽

Scientific Article ◽

Socioeconomic Groups ◽

Universal Healthcare ◽

Healthcare Coverage ◽

Universal Healthcare Coverage

IntroductionEven in advanced economies with universal healthcare coverage (UHC), a social gradient in healthcare utilisation has been reported. Many individual, community and healthcare system factors have been considered that may be associated with the variation in healthcare utilisation between socioeconomic groups. Nevertheless, relatively little is known about the complex interaction and relative contribution of these factors to socioeconomic differences in healthcare utilisation. In order to improve understanding of why utilisation patterns differ by socioeconomic status (SES), the proposed systematic review will explore the main mechanisms that have been examined in quantitative research.Methods and analysisThe systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines and will be conducted in Embase, PubMed, Scopus, Web of Science, Econlit and PsycInfo. Articles examining factors associated with the differences in primary and specialised healthcare utilisation between socioeconomic groups in Organisation for Economic Co-operation and Development (OECD) countries with UHC will be included. Further restrictions concern specifications of outcome measures, factors of interest, study design, population, language and type of publication. Data will be numerically summarised, narratively synthesised and thematically discussed. The factors will be categorised according to existing frameworks for barriers to healthcare access.Ethics and disseminationNo primary data will be collected. No ethics approval is required. We intend to publish a scientific article in an international peer-reviewed journal.

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Health inequalities in hospitalisation and mortality in patients diagnosed with heart failure in a universal healthcare coverage system

Journal of Epidemiology & Community Health ◽

10.1136/jech-2017-210146 ◽

2018 ◽

Vol 72 (9) ◽

pp. 845-851 ◽

Cited By ~ 4

Author(s):

Raquel Garcia ◽

Rosa Abellana ◽

Jordi Real ◽

José-Luis del Val ◽

Jose Maria Verdú-Rotellar ◽

...

Keyword(s):

Heart Failure ◽

Total Mortality ◽

Community Dwelling ◽

Socioeconomic Groups ◽

Universal Healthcare ◽

Cox Proportional Hazard ◽

Increased Risk ◽

Healthcare Coverage ◽

Cox Proportional Hazard Models ◽

Universal Healthcare Coverage

BackgroundInformation regarding the effect of social determinants of health on heart failure (HF) community-dwelling patients is scarce. We aimed to analyse the presence of socioeconomic inequalities, and their impact on hospitalisations and mortality, in patients with HF attended in a universal healthcare coverage system.MethodsA retrospective cohort study carried out in patients with HF aged >40 and attended at the 53 primary healthcare centres of the Institut Català de la Salut in Barcelona (Spain). Socioeconomic status (SES) was determined by an aggregated deprivation index (MEDEA). Cox proportional hazard models and competing-risks regression based on Fine and Gray’s proportional subhazards were performed to analyse hospitalisations due to of HF and total mortality that occurred between 1 January 2009 and 31 December 2012.ResultsMean age was 78.1 years (SD 10.2) and 56% were women. Among the 8235 patients included, 19.4% died during the 4 years of follow-up and 27.1% were hospitalised due to HF. A gradient in the risk of hospitalisation was observed according to SES with the highest risk in the lowest socioeconomic group (sHR 1.46, 95% CI 1.27 to 1.68). Nevertheless, overall mortality did not differ among the socioeconomic groups.ConclusionsIn spite of finding a gradient that linked socioeconomic deprivation to an increased risk of hospitalisation, there were no differences in mortality regarding SES in a universal healthcare coverage system.

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Evidences supporting the inclusion of immigrants in the universal healthcare coverage

European Journal of Public Health ◽

10.1093/eurpub/ckaa020 ◽

2020 ◽

Vol 30 (4) ◽

pp. 785-787

Author(s):

Albert Prats-Uribe ◽

Sílvia Brugueras ◽

Dolors Comet ◽

Dolores Álamo-Junquera ◽

LLuïsa Ortega Gutiérrez ◽

...

Keyword(s):

Diabetes Mellitus ◽

Heart Failure ◽

Infectious Diseases ◽

Chronic Obstructive ◽

Matched Sample ◽

Obstructive Pulmonary Disease ◽

Universal Healthcare ◽

Primary Health ◽

Healthcare Coverage ◽

Universal Healthcare Coverage

Abstract In 2012, the Spanish government enforced a healthcare exclusion policy against undocumented immigrants. The newly elected government has recently derogated this policy. To analyze how this decree could have affected population health, we looked at primary health patients who would have been excluded and compared with a matched sample of non-excluded patients. Potentially excluded patients had decreased odds of: depression, chronic obstructive pulmonary disease, dyslipidaemia, heart failure and hypertension while diabetes mellitus rates were similar to non-excluded. Infectious diseases were more frequent in potentially excluded population (HIV, tuberculosis and syphilis). The exclusion of patients impedes the control of infectious diseases at a community level.

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