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  1. Hussain-Alkhateeb L, Kroeger A, Olliaro P, Rocklöv J, Sewe MO, Tejeda G, et al.
    PLoS One, 2018;13(5):e0196811.
    PMID: 29727447 DOI: 10.1371/journal.pone.0196811
    BACKGROUND: Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level.

    METHODS: We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico.

    FINDINGS: 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion.

    CONCLUSION: EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

  2. Jovanović V, Rudnev M, Abdelrahman M, Abdul Kadir NB, Adebayo DF, Akaliyski P, et al.
    Psychol Assess, 2024 Jan;36(1):14-29.
    PMID: 38010780 DOI: 10.1037/pas0001270
    Coronavirus Anxiety Scale (CAS) is a widely used measure that captures somatic symptoms of coronavirus-related anxiety. In a large-scale collaboration spanning 60 countries (Ntotal = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
  3. Karakulak A, Tepe B, Dimitrova R, Abdelrahman M, Akaliyski P, Alaseel R, et al.
    Commun Psychol, 2023 Dec 15;1(1):43.
    PMID: 39242865 DOI: 10.1038/s44271-023-00046-5
    With the COVID-19 pandemic, behavioural scientists aimed to illuminate reasons why people comply with (or not) large-scale cooperative activities. Here we investigated the motives that underlie support for COVID-19 preventive behaviours in a sample of 12,758 individuals from 34 countries. We hypothesized that the associations of empathic prosocial concern and fear of disease with support towards preventive COVID-19 behaviours would be moderated by trust in the government. Results suggest that the association between fear of disease and support for COVID-19 preventive behaviours was strongest when trust in the government was weak (both at individual- and country-level). Conversely, the association with empathic prosocial concern was strongest when trust in the government was high, but this moderation was only found at individual-level scores of governmental trust. We discuss how motivations may be shaped by socio-cultural context, and outline how findings may contribute to a better understanding of collective action during global crises.
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