Changes in reproductive, maternal, and child health in Haiti during the pre- and peri-COVID-19 pandemic / Cambios en materia de salud reproductiva, materna e infantil en los periodos pre y peripandémico de la COVID-19 en Haití / Mudanças na saúde reprodutiva, materna e infantil no Haiti antes e durante a pandemia de COVID-19

[ABSTRACT]. Objective. To assess changes in reproductive, maternal, newborn, child, and adolescent health (RMNCAH) in Haiti from August 2018 to September 2021, before and during the COVID-19 pandemic. Methods. A retrospective study using surveillance data from the Haitian Unique Health Information System, examining two periods: pre- and peri-COVID-19 pandemic. Health indicators at the national level in the two periods were compared using two-sample t-tests for proportions, and average absolute monthly changes were calculated using variance-weighted regression. Results. There was a statistically significant decline in the proportion of most of the indicators assessed from the pre- to the peri-COVID-19 pandemic period. However, the most affected indicators were the proportions of pregnant women with four antenatal care visits, with five antenatal care visits or more, and those who received a second dose of tetanus vaccine, which decreased by over 4 percentage points during the two periods. Likewise, the proportions of children who received diphtheria, tetanus, and pertussis (DTaP), BCG, polio, pentavalent, and rotavirus vaccines also all declined by over 8 percentage points. In contrast, pneu- mococcal conjugate vaccine increased by over 4 percentage points. A statistically significant decrease was also observed in the average absolute monthly changes of several reproductive and child health indicators assessed. Conclusions. The COVID-19 pandemic may have contributed to the decline observed in several RMNCAH indicators in Haiti. However, the role played by the sociopolitical crisis and control exercised by armed groups over the population in the last three years cannot be ruled out.

[RESUMEN]. Objetivo. Evaluar los cambios en materia de salud reproductiva, materna, neonatal, infantil y adolescente que se produjeron en Haití desde agosto del 2018 hasta septiembre del 2021, antes de la pandemia de COVID-19 y durante ella. Metodología. Estudio retrospectivo basado en datos de vigilancia del sistema único de información de salud de Haití para estudiar los periodos pre y peripandémico. La comparación de los indicadores de salud a nivel nacional de estos dos periodos se realizó mediante pruebas de t de dos muestras para comparar proporciones, y se calculó el promedio de la variación mensual absoluta mediante una regresión ponderada por la varianza. Resultados. Al comparar el periodo prepandémico con el peripandémico, se observó un descenso estadísticamente significativo de la mayoría de los indicadores porcentuales evaluados. Sin embargo, los indicadores porcentuales más afectados fueron los de mujeres embarazadas con cuatro visitas de atención prenatal, con cinco visitas de atención prenatal o más, o que recibieron una segunda dosis de la vacuna contra el tétanos; estos indicadores disminuyeron en más de cuatro puntos porcentuales en el segundo periodo en comparación con el primero. Asimismo, las proporciones de niños y niñas que recibieron las vacunas contra la difteria, el tétanos y la tosferina (DTPa), contra la poliomielitis, antirrotavírica, BCG, y pentavalente también disminuyeron en más de ocho puntos porcentuales. En cambio, la proporción de niños y niñas que recibieron la vacuna antineumocócica conjugada aumentó en más de cuatro puntos porcentuales. También se observó un descenso estadísticamente significativo en el promedio de la variación mensual absoluta de varios indicadores de salud reproductiva e infantil. Conclusiones. La pandemia de COVID-19 puede haber contribuido al descenso observado en varios indica- dores relacionados con la salud reproductiva, materna, neonatal, infantil y adolescente en Haití. Sin embargo, no se puede descartar el papel que ha desempeñado en dicho descenso la crisis sociopolítica y el control ejercido por los grupos armados sobre la población en los últimos tres años.

[RESUMO]. Objetivo. Avaliar mudanças na saúde reprodutiva, materna, neonatal, da criança e do adolescente no Haiti entre agosto de 2018 e setembro de 2021, antes e durante a pandemia de COVID-19. Métodos. Estudo retrospectivo usando dados de vigilância do Sistema Único de Informações de Saúde do Haiti, examinando dois períodos, antes e durante a pandemia de COVID-19. Os indicadores de saúde do país nos dois períodos foram comparados por meio de testes t de duas amostras para proporções, e as variações mensais absolutas médias foram calculadas por meio de regressão linear ponderada. Resultados. Entre o período anterior e o período durante a pandemia de COVID-19, houve uma queda estatisticamente significante na proporção da maioria dos indicadores avaliados. Os indicadores mais afetados, porém, foram as proporções de gestantes com quatro consultas de pré-natal, gestantes com cinco ou mais consultas de pré-natal e gestantes que receberam uma segunda dose de vacina antitetânica, que sofreram uma diminuição de mais de 4 pontos percentuais na comparação entre os dois períodos. Similarmente, as proporções de crianças que receberam vacinas contra difteria, tétano e pertússis (DTPa), BCG, poliomielite, pentavalente e rotavírus também diminuíram em mais de 8 pontos percentuais. Por outro lado, no caso da vacina pneumocócica conjugada houve um aumento de mais de 4 pontos percentuais. Além disso, foi observada uma redução estatisticamente significante nas variações mensais absolutas médias de vários indicadores de saúde reprodutiva e infantil avaliados. Conclusões. A pandemia de COVID-19 pode ter contribuído para a piora observada em vários indicadores de saúde reprodutiva, materna, neonatal, da criança e do adolescente no Haiti. No entanto, não se pode descartar o papel desempenhado pela crise sociopolítica e pelo controle exercido por grupos armados sobre a população nos últimos três anos.

A study on deep learning model based on global-local structure for crowd flow prediction.

Crowd flow prediction has been studied for a variety of purposes, ranging from the private sector such as location selection of stores according to the characteristics of commercial districts and customer-tailored marketing to the public sector for social infrastructure design such as transportation networks. Its importance is even greater in light of the spread of contagious diseases such as COVID-19. In many cases, crowd flow can be divided into subgroups by common characteristics such as gender, age, location type, etc. If we use such hierarchical structure of the data effectively, we can improve prediction accuracy of crowd flow for subgroups. But the existing prediction models do not consider such hierarchical structure of the data. In this study, we propose a deep learning model based on global-local structure of the crowd flow data, which utilizes the overall(global) and subdivided by the types of sites(local) crowd flow data simultaneously to predict the crowd flow of each subgroup. The experiment result shows that the proposed model improves the prediction accuracy of each sub-divided subgroup by 5.2% (Table 5 Cat #9)-45.95% (Table 11 Cat #5), depending on the data set. This result comes from the comparison with the related works under the same condition that use target category data to predict each subgroup. In addition, when we refine the global data composition by considering the correlation between subgroups and excluding low correlated subgroups, the prediction accuracy is further improved by 5.6-48.65%.

Neuropathological lesions in intravenous BCG-stimulated K18-hACE2 mice challenged with SARS-CoV-2.

In the wake of the COVID-19 pandemic caused by SARS-CoV-2, questions emerged about the potential effects of Bacillus Calmette-Guérin (BCG) vaccine on the immune response to SARS-CoV-2 infection, including the neurodegenerative diseases it may contribute to. To explore this, an experimental study was carried out in BCG-stimulated and non-stimulated k18-hACE2 mice challenged with SARS-CoV-2. Viral loads in tissues determined by RT-qPCR, histopathology in brain and lungs, immunohistochemical study in brain (IHC) as well as mortality rates, clinical signs and plasma inflammatory and coagulation biomarkers were assessed. Our results showed BCG-SARS-CoV-2 challenged mice presented higher viral loads in the brain and an increased frequency of neuroinvasion, with the greatest differences observed between groups at 3-4 days post-infection (dpi). Histopathological examination showed a higher severity of brain lesions in BCG-SARS-CoV-2 challenged mice, mainly consisting of neuroinflammation, increased glial cell population and neuronal degeneration, from 5 dpi onwards. This group also presented higher interstitial pneumonia and vascular thrombosis in lungs (3-4 dpi), BCG-SARS-CoV-2 mice showed higher values for TNF-α and D-dimer values, while iNOS values were higher in SARS-CoV-2 mice at 3-4 dpi. Results presented in this study indicate that BCG stimulation could have intensified the inflammatory and neurodegenerative lesions promoting virus neuroinvasion and dissemination in this experimental model. Although k18-hACE2 mice show higher hACE2 expression and neurodissemination, this study suggests that, although the benefits of BCG on enhancing heterologous protection against pathogens and tumour cells have been broadly demonstrated, potential adverse outcomes due to the non-specific effects of BCG should be considered.

Development and validation of a prognostic model for assessing long COVID risk following Omicron wave-a large population-based cohort study.

BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.

Informing evidence-based policy during the COVID-19 pandemic and recovery period: learning from a national evidence centre.

BACKGROUND: The COVID-19 pandemic demonstrated the vital need for research to inform policy decision-making and save lives. The Wales COVID-19 Evidence Centre (WCEC) was established in March 2021 and funded for two years, to make evidence about the impact of the pandemic and ongoing research priorities for Wales available and actionable to policy decision-makers, service leads and the public. OBJECTIVES: We describe the approaches we developed and our experiences, challenges and future vision. PROGRAM IMPLEMENTATION: The centre operated with a core team, including a public partnership group, and six experienced research groups as collaborating partners. Our rapid evidence delivery process had five stages: 1. Stakeholder engagement (continued throughout all stages); 2. Research question prioritisation; 3. Bespoke rapid evidence review methodology in a phased approach; 4. Rapid primary research; and 5. Knowledge Mobilisation to ensure the evidence was available for decision-makers. MAIN ACHIEVEMENTS: Between March 2021-23 we engaged with 44 stakeholder groups, completed 35 Rapid Evidence Reviews, six Rapid Evidence Maps and 10 Rapid Evidence Summaries. We completed four primary research studies, with three published in peer reviewed journals, and seven ongoing. Our evidence informed policy decision-making and was cited in 19 Welsh Government papers. These included pandemic infection control measures, the Action Plan to tackle gender inequalities, and Education Renew and Reform policy. We conducted 24 Welsh Government evidence briefings and three public facing symposia. POLICY IMPLICATIONS: Strong engagement with stakeholder groups, a phased rapid evidence review approach, and primary research to address key gaps in current knowledge enabled high-quality efficient, evidence outputs to be delivered to help inform Welsh policy decision-making during the pandemic. We learn from these processes to continue to deliver evidence from March 2023 as the Health and Care Research Wales Evidence Centre, with a broader remit of health and social care, to help inform policy and practice decisions during the recovery phase and beyond.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance.

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

Prevalence and Severity of COVID-19 among Pediatric Patients with Atopy: A Cross-sectional Study in Kerman, Southeast Iran.

The tragic COVID-19 pandemic affected many children worldwide. Among the factors that may influence the course of viral infections including COVID-19, it is still uncertain whether atopy has a protective or predisposing role. The study aims to address the knowledge gap by investigating the prevalence and severity of COVID-19 among atopic children in Kerman, in 2022. A descriptive-analytical cross-sectional study on children with a history of atopy was performed in Kerman Medical University. Demographic information, type of atopy (including allergic rhinitis, Hyper-Reactive Airway Disease (HRAD) or asthma, eczema, urticaria, anaphylaxis, and food allergy), history of COVID-19 infection, and disease severity were recorded. A total of 1007 children and adolescents, (boys: 56.4%, girls: 43.6%, age:5.61±2.64 years) were included in the study. History of COVID-19 infection was positive in 53.5%, with 75.9% of the cases exhibiting mild disease severity. The frequency of atopies was HRAD or asthma (67.2%), allergic rhinitis (42.6%), and food allergy (27.4%). The frequency of COVID-19 cases was significantly higher among patients with HRAD or asthma, whereas it was significantly lower among those with food allergies, anaphylaxis, and eczema. Among atopic individuals, COVID-19 severity was significantly lower in those with allergic rhinitis, while the opposite trend was observed among food-allergic individuals. This study sheds light on the relationship between atopy and COVID-19 among pediatric patients. It seems specific types of atopies may influence the risk and severity of COVID-19 infection differently. A better understanding of these associations can inform clinical management and preventive measures for vulnerable pediatric populations.

Antibody Response Before and After the Booster Dose of Inactivated Corona Vaccine in Antibody Deficient Patients.

Patients with inborn errors of immunity (IEI) are among the high-risk groups regarding COVID-19. Receiving booster doses (third and fourth) in addition to the standard doses is recommended in these patients. This study investigated the antibody response before and after a booster dose of Sinopharm vaccine in IEI patients.  Thirty patients (>12 years) with antibody deficiencies, referred to Imam Khomeini Hospital and Children's Medical Center in Tehran, were enrolled in this prospective cross-sectional study. All patients were fully vaccinated with the BBIBP-CorV vaccine (2 doses of Sinopharm). Initial measurements of anti-receptor-binding domain (anti-RBD) and anti-nucleocapsid (anti-N) IgG antibody responses were conducted by enzyme-linked immunosorbent assay (ELISA). Subsequently, all patients received a booster dose of the vaccine. Four to six weeks after booster injection, the levels of antibodies were re-evaluated.  Twenty patients with common variable immunodeficiency (CVID), 7 cases with agammaglobulinemia and 3 patients with hyper IgM syndrome were studied. Anti-RBD IgG and anti-N IgG antibodies increased in all patients after the booster. Our results indicated the need of receiving booster doses of the COVID-19 vaccine in patients with antibody deficiencies, even for enhancing humoral immune response specially in patients with CVID.

Proton pump inhibitors and gastrointestinal symptoms among patients with COVID-19 infection.

INTRODUCTION: The administration of proton pump inhibitors (PPIs) is anticipated to elevate an individual's susceptibility to enteric infections as a result of altering the gut flora. The influence of PPIs on the clinical manifestation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still uncertain. This study aims to investigate the impact of PPI usage on the clinical manifestation of COVID-19, namely its gastrointestinal symptoms. METHODS: This is a cross-sectional cohort study involving COVID-19 patients. Patients were interviewed using a predesigned questionnaire that asked about their demographics, clinical manifestations of COVID-19 infection, and the extent and type of PPIs in use. PPI usage was confirmed by reviewing patients' electronic medical records. The primary outcome was to establish any association between the use of PPI and the symptoms and clinical presentation of COVID-19. RESULTS: Out of a total of 254 participants, 69 (27.2%) were considered PPI users. Patients who were on PPI medications reported a significantly lower rate of myalgia (27.5% vs 51.9%; p = 0.0006) and heartburn (5.7% vs 15.6%; p = 0.03) but had a significantly higher rate of abdominal pain (27.5% vs 13.5%; p = 0.001) and diarrhoea (28.9% vs 14.5%, p = 0.02) when compared to those who were not using PPIs. Patients on PPIs were also shown to have significantly higher odds of developing diarrhoea (OR 2.0, 95% CI: 1.08 to 3.93, p = 0.02) and abdominal pain (OR 2.0, 95% CI: 1.22 to 3.93, p = 0.03), but a lower risk of developing myalgia (OR 0.5, 95% CI: 0.3 to 0.9, p = 0.02) when compared to non-PPI users. CONCLUSION: This study shows that the use of PPIs could impact COVID-19 clinical presentation toward more gastrointestinal manifestations. Further studies investigating the link between other acid suppression medications and COVID-19 manifestations and severity should be carried out.

School closures and prescription medication use among children and adolescents before and during the COVID-19 pandemic in the USA, 2019-2022.

The impact of schools closing for in-person instruction in the USA during the COVID-19 pandemic on the use of prescription medications is not known. In this study, we examined changes in the total prescriptions filled, specifically for attention deficit hyperactivity disorder (ADHD) medications, among school-aged children and adolescents aged 10-19 years during periods before and after complete school closures between October 2019 and September 2022. Our findings indicate that complete school closures were associated with declines in the use of ADHD medications among younger populations in the USA. These findings suggest that the underuse of ADHD medications may be an overlooked contributor to declines in academic performance observed during periods of school closures during the COVID-19 pandemic.

The Declaration of the National Emergency in Child and Adolescent Mental Health: It Takes a Village.

Recognition of the high prevalence of children's mental health conditions and challenges to accessing needed care faced by children and their families have been long-standing concerns, emerging well before the onset of the COVID-19 pandemic. Global data examining the prevalence of at least one mental health and/or substance-use disorder for 2516 million people aged 5 to 24 years in 2019 found that at least 293 million people were affected by at least one mental health disorder and 31 million affected by a substance-use disorder.

Impact of COVID-19 pandemic on neurodevelopmental outcomes of premature infants: a retrospective national cohort study.

OBJECTIVE: To compare the neurodevelopmental outcomes of preterm infants before and during the COVID-19 pandemic. DESIGN: Premature infants born in 2018 were assigned to the pre-pandemic group, while those born in 2019 were assigned to the during-pandemic group. SETTING: Nationwide cohort study. PATIENTS: Very low birthweight premature infants registered in the Taiwan Premature Infant Follow-up Network database. INTERVENTIONS: Anti-epidemic measures, including quarantine and isolation protocols, social distancing, the closure of public spaces and restrictions on travel and gatherings during COVID-19 pandemic. MAIN OUTCOME MEASURES: Outcomes were measured by Bayley Scales of Infant and Toddler Development Third Edition at corrected ages of 6, 12 and 24 months old. Generalised estimating equation (GEE) was applied to incorporate all measurements into a single model. RESULTS: Among the 1939 premature infants who were enrolled, 985 developed before the pandemic, while 954 developed during the pandemic. Premature infants whose development occurred during the pandemic exhibited better cognitive composite at the corrected age of 6 months (beta=2.358; 95% CI, 1.07 to 3.65; p<0.001), and motor composite at corrected ages of 12 months (beta=1.680; 95% CI, 0.34 to 3.02; p=0.014). GEE analysis showed that infants who had grown during the pandemic achieved higher scores in cognitive composite (beta=1.416; 95% CI, 0.36 to 2.48; p=0.009). CONCLUSION: Premature infants in Taiwan who developed during the pandemic showed better neurodevelopment compared with those born before the pandemic.

Using Advocacy to Address the Crisis of Children's Mental Health.

Children and youth in the United States are experiencing a mental health crisis that predates the COVID-19 pandemic. Child and adolescent psychiatrists have the knowledge and skillset to advocate for improving the pediatric mental health care system at the local, state, and federal levels. Child psychiatrists can use their knowledge and expertise to advocate legislatively or through regulatory advocacy to improve access to mental health care for youth. Further, including advocacy education in psychiatry and child psychiatry graduate medical education would help empower child psychiatrists to make an impact through their advocacy efforts.

A deep learning-based model for detecting Leishmania amastigotes in microscopic slides: a new approach to telemedicine.

BACKGROUND: Leishmaniasis, an illness caused by protozoa, accounts for a substantial number of human fatalities globally, thereby emerging as one of the most fatal parasitic diseases. The conventional methods employed for detecting the Leishmania parasite through microscopy are not only time-consuming but also susceptible to errors. Therefore, the main objective of this study is to develop a model based on deep learning, a subfield of artificial intelligence, that could facilitate automated diagnosis of leishmaniasis. METHODS: In this research, we introduce LeishFuNet, a deep learning framework designed for detecting Leishmania parasites in microscopic images. To enhance the performance of our model through same-domain transfer learning, we initially train four distinct models: VGG19, ResNet50, MobileNetV2, and DenseNet 169 on a dataset related to another infectious disease, COVID-19. These trained models are then utilized as new pre-trained models and fine-tuned on a set of 292 self-collected high-resolution microscopic images, consisting of 138 positive cases and 154 negative cases. The final prediction is generated through the fusion of information analyzed by these pre-trained models. Grad-CAM, an explainable artificial intelligence technique, is implemented to demonstrate the model's interpretability. RESULTS: The final results of utilizing our model for detecting amastigotes in microscopic images are as follows: accuracy of 98.95 1.4%, specificity of 98 2.67%, sensitivity of 100%, precision of 97.91 2.77%, F1-score of 98.92 1.43%, and Area Under Receiver Operating Characteristic Curve of 99 1.33. CONCLUSION: The newly devised system is precise, swift, user-friendly, and economical, thus indicating the potential of deep learning as a substitute for the prevailing leishmanial diagnostic techniques.

Development and validity evidence on the scale of perceived social support for university students (EPSSEU) during the period of social restrictions.

AIM: This study aims to validate a Perceived Social Support Scale for University Students (EPSSEU) during periods of social restrictions, by focusing on family and university support. SUBJECT AND METHODS: This cross-sectional study was conducted with undergraduate students from a public higher education institution. The college students who participated in the study-1353 at baseline and 378 after 6 months-answered a virtual questionnaire containing questions on: sociodemographic and lifestyle data, items proposed for the EPSSEU, Satisfaction with Social Support Scale (ESSS), and Depression, Anxiety and Stress Scale (DASS-21). Exploratory factor analysis, Cronbach's alpha reliability analysis, as well as discriminant, convergent, and known-group validations were performed. RESULTS: The results showed two factors support from: i) the university and ii) friends and family- which explained 61.82% of the variance in the data. The EPSSEU showed good reliability (Cronbach's alpha = 0.796) as well as validity, with higher scores among individuals without depression, anxiety, or stress. CONCLUSION: The EPSSEU shows adequate psychometric qualities and may be a useful instrument for assessing university students' social support in pandemics, social distancing, and remote teaching contexts.