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Psychosocial impacts of COVID-19 in the Guinean population. An online cross-sectional survey.

Guinea, like many other African countries, has been facing an unprecedented COVID-19 outbreak, since March 2020. In April 2020, Guinean National agency for health security recorded 1351 confirmed cases of COVID-19, including 313 recoveries and 07 deaths. To address this health crisis, some drastic measures were implemented to prevent the spread of COVID-19. Those measures might potentially cause some psychological problems among Guineans. Thus, we conducted this study to assess the psychosocial impacts of COVID-19 in the Guinean population. We carried out an online cross-sectional survey among internet users in Guinea. A free e-survey platform was used, and questionnaires were sent to internet users. The study ran from May 1 through May 10 2020. Participation in the study was voluntary. Data collection was based on sociodemographic information and self-reported questionnaires: Impact of Event Scale-Revised (IES-R) for stress evaluation, Penn state worry questionnaire (PSWQ), and an adapted Social Psychological Measurements of COVID-19. A total of 280 participants took part in the study; responses from 5 participants were deleted because of incompleteness. The average age of participants was 28.9 [95% CI: 28.1;29.6]. Most of participants were male 65.5% [95% CI: 59.5%;71.1%]. Unemployed participants stood for 48.7% [95% CI: 42.7%;54.8%]. IES-R scale for stress evaluation yielded the following findings: 19.6% (mild), 5.23% (moderate) and 9.15% (severe); 82.8% and 17.2% of participants had respectively reported low and moderate worry. No significant statistical association was found between sociodemographic variables and traumatic events (IES-R and PSWQ). However, 82% of our participants had to cope with the negative impacts of COVID-19. Although there were few cases of traumatic events, negative impacts of COVID-19 on study participants deserve to be underlined. So, further investigations are necessary to identify and disentangle specific psychosocial problems in different Guinean socio-cultural contexts

Haematological and Biochemical Reference Values for Healthy Population of Maferinyah Rural Community in Guinea

Guinea’s reference ranges for biological parameters rely on those of Caucasian values. Variability in reference ranges according to the context is well-documented. We conducted this study for the purpose of future malaria clinical trials that assess the efficacy and safety of malaria drugs. A repeated cross-sectional study was carried out, in an apparently healthy cohort population. Surveys took place in Maferinyah rural community, which is located at 75 km from the capital. The 2.5th and 97.5th percentiles were determined nonparametrically and stood for reference intervals. Reference values were determined separately for males and females according to ranges of age (6-10 years of age; 11-15 years of age; 16-45 years of age). Differences between genders were tested using the Mann-Whitney test, while the Friedman test was performed to test differences within each gender group according to the seasons. A total of 450 volunteers were enrolled. The median age was 13. Males 16-45 years of age had significantly higher hematologic and biochemical values compared to a female of the same age (for hematological parameters: Mean Cell Hemoglobin Concentration MCHC p≤0.001, Platelets p≤0.001, monocytes p=0.0305, eosinophils p=0.0225; for biochemical parameters: Aspartate aminotransferase AST p≤0.001, Alanine Aminotransferase ALT p≤0.001, creatinine p≤0.001). We noticed significant seasonal variations for all the biochemical parameters and some hematologic parameters (Mean Corpuscular Hemoglobin MCH, MCHC, Mean Cell volume). This is the first study establishing hematologic and biochemical parameters in Guinea. These findings provide a useful guide for the clinical researchers and care providers. Studies on large scale and in different settings would be also desirable

Evaluation of maternal and child care continuum in Guinea: a secondary analysis of two demographic and health surveys using the composite coverage index (CCI)

International audienceIntroduction: The composite coverage index (CCI) is the weighted average coverage of eight preventive and curative interventions received along the maternal and childcare continuum. This study aimed to analyse maternal and child health indicators using CCI.Methods: We performed a secondary analysis of demographic and health surveys (DHS) focused on women aged 15 to 49 and their children aged 1 to 4. This study took place in Guinea. The CCI (meeting the need for planning, childbirth assisted by qualified healthcare workers, antenatal care assisted by qualified healthcare workers, vaccination against diphtheria, pertussis, tetanus, measles and Bacillus Calmette-Guérin, taking oral rehydration salts during diarrhoea and seeking care for pneumonia) is optimal if the weighted proportion of interventions is > 50%; otherwise, it is partial. We identified the factors associated with CCI using the descriptive association tests, the spatial autocorrelation statistic and multivariate logistic regression.Results: The analyses involved two DHS surveys, with 3034 included in 2012 and 4212 in 2018. The optimal coverage of the CCI has increased from 43% in 2012 to 61% in 2018. In multivariate analysis, in 2012: the poor had a lower probability of having an optimal CCI than the richest; OR = 0.11 [95% CI; 0.07, 0.18]. Those who had done four antenatal care visits (ANC) were 2.78 times more likely to have an optimal CCI than those with less OR = 2.78 [95% CI;2.24, 3.45]. In 2018: the poor had a lower probability of having an optimal CCI than the richest OR = 0.27 [95% CI; 0.19, 0.38]. Women who planned their pregnancies were 28% more likely to have an optimal CCI than those who had not planned OR = 1.28 [95% CI;1.05, 1.56]. Finally, women with more than 4 ANC were 2.43 times more likely to have an optimal CCI than those with the least OR = 2.43 [95% CI; 2.03, 2.90]. The spatial analysis reveals significant disparities with an aggregation of high partial CCI in Labé between 2012 and 2018.Conclusion: This study showed an increase in CCI between 2012 and 2018. Policies should improve access to care and information for poor women. Besides, strengthening ANC visits and reducing regional inequalities increases optimal CCI