National, regional, and global estimates of low birthweight in 2020, with trends from 2000: a systematic analysis.

BACKGROUND: Low birthweight (LBW; <2500 g) is an important predictor of health outcomes throughout the life course. We aimed to update country, regional, and global estimates of LBW prevalence for 2020, with trends from 2000, to assess progress towards global targets to reduce LBW by 30% by 2030. METHODS: For this systematic analysis, we searched population-based, nationally representative data on LBW from Jan 1, 2000, to Dec 31, 2020. Using 2042 administrative and survey datapoints from 158 countries and areas, we developed a Bayesian hierarchical regression model incorporating country-specific intercepts, time-varying covariates, non-linear time trends, and bias adjustments based on data quality. We also provided novel estimates by birthweight subgroups. FINDINGS: An estimated 19·8 million (95% credible interval 18·4-21·7 million) or 14·7% (13·7-16·1) of liveborn newborns were LBW worldwide in 2020, compared with 22·1 million (20·7-23·9 million) and 16·6% (15·5-17·9) in 2000-an absolute reduction of 1·9 percentage points between 2000 and 2020. Using 2012 as the baseline, as this is when the Global Nutrition Target began, the estimated average annual rate of reduction from 2012 to 2020 was 0·3% worldwide, 0·85% in southern Asia, and 0·59% in sub-Saharan Africa. Nearly three-quarters of LBW births in 2020 occurred in these two regions: of 19 833 900 estimated LBW births worldwide, 8 817 000 (44·5%) were in southern Asia and 5 381 300 (27·1%) were in sub-Saharan Africa. Of 945 300 estimated LBW births in northern America, Australia and New Zealand, central Asia, and Europe, approximately 35·0% (323 700) weighed less than 2000 g: 5·8% (95% CI 5·2-6·4; 54 800 [95% CI 49 400-60 800]) weighed less than 1000 g, 9·0% (8·7-9·4; 85 400 [82 000-88 900]) weighed between 1000 g and 1499 g, and 19·4% (19·0-19·8; 183 500 [180 000-187 000]) weighed between 1500 g and 1999 g. INTERPRETATION: Insufficient progress has occurred over the past two decades to meet the Global Nutrition Target of a 30% reduction in LBW between 2012 and 2030. Accelerating progress requires investments throughout the lifecycle focused on primary prevention, especially for adolescent girls and women living in the most affected countries. With increasing numbers of births in facilities and advancing electronic information systems, improvements in the quality and availability of administrative LBW data are also achievable. FUNDING: The Children's Investment Fund Foundation; the UNDP-UNFPA-UNICEF-WHO World Bank Special Programme of Research, Development and Research Training in Human Reproduction; and the Bill & Melinda Gates Foundation.

Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks.

Introduction: Dengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels. Methods: The validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality. Results: The study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI). Discussion: The tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction.

Community perception of causes of death using verbal autopsy for diabetes mellitus in Saudi Arabia.

Diabetes mellitus is a serious global health issue which significantly impacts public health and socioeconomic development. Exploring how the community perceives the causes of death and their associated risk factors is crucial for public health. This study combines verbal autopsy (VA) with the Type 2 Diabetes Mellitus (T2DM) register to explore community perceptions of causes of death and associated influential factors in Makkah province, Saudi Arabia. 302 VA interviews were conducted with relatives or caregivers of deceased who died between 2018 and 2021 based on T2DM medical register from Alnoor Specialist Hospital in Makkah City, Saudi Arabia. Cause-specific mortality fractions (CSMFs) obtained from the VA using the InterVA-5 model were utilized to assess community perception. We used a multivariable logistic regression model to determine factors influencing community perceptions of causes of death. Lin's CCC with 95% CI was used to analyze the concordance for the CSMFs from verbal autopsy causes of death (VACoD) as a presumed reference standard and family-reported causes of death (FRCoD). The outcomes of this study demonstrate a generally broad spectrum of community perceived mortalities, with some critical misconceptions based on the type of death and other vital events like marital status, with an overall CCC of 0.60 (95% CI: 0.20-1.00; p = 003). The study findings demonstrate that community perception is weak if the deceased was male compared to female (aOR: 0.52; 95% CI: 0.26-1.03) and if the deceased was > = 80 years compared to 34-59 years (aOR: 0.48; 95% CI: 0.16-1.38), but it significantly improves among married compared to single (aOR: 2.13; 95% CI: 1.02-4.42). Exploring community perception of causes of death is crucial as it provides valuable insights into the community's understanding, beliefs, and concerns regarding mortality. Higher or lower community perception is attributed to how people may perceive risk factors associated with the causes of death, which can guide public health planning and interventional programs. The study findings further emphasize the need to employ robust and standardized VA methods within the routine medical services for a systemized assessment of families' reported causes of death.

Community pharmacists' perspectives towards automated pharmacy systems and extended community pharmacy services: An online cross-sectional study.

Background: Private sector partnerships through community pharmacies are essential for effective healthcare integration to achieve the United Nations 2030 Agenda for Sustainable Development Goals. This partnership can provide significant clinical outcomes and reduce health system expenditures by delivering services focused on patient-centred care, such as public health screening and medication therapy management. Objectives: To assess the understanding of the proposed strategic and health system reform in Saudi Arabia by exploring community pharmacists' perspectives towards the capacity and readiness of community pharmacies to use automated pharmacy systems, provide extended community pharmacy services, and identify perceived barriers. Materials and methods: This multicentre, cross-sectional, web-based survey was conducted in Saudi Arabia (October-December 2021). Graphical and numerical statistics were used to describe key dimensions by the background and characteristics of the respondents, and multiple ordinal logistic regression analyses were sought to assess their associations. Results: Of the 403 consenting and participating community pharmacists, most were male (94%), belonged to chain pharmacies (77%), and worked >48 h per week (72%). Automated pharmacy systems, such as electronic prescriptions, were never utilised (50%), and health screening services, such as blood glucose (76%) and blood pressure measurement (74%), were never provided. Services for medication therapy management were somewhat limited. Age groups ≤40 years, chain pharmacies, >10 years of experience and ≥ 3 pharmacists in place with <100 daily medication prescriptions and Jazan province were significantly more likely to provide all medication therapy management services than others. Operational factors were the barriers most significantly associated with the independent variables. Conclusion: The results showed that most services and automated pharmacy systems remained limited and well-needed. When attempting to implement these services to drive change, community pharmacies face numerous challenges, and urgent efforts by private and government sectors are essential to improve pharmaceutical care in community pharmacy settings.

Public perspective toward extended community pharmacy services in sub-national Saudi Arabia: An online cross-sectional study.

BACKGROUND: In many developed countries, the scope of community pharmacy services has extended to include advanced applications. Unlike traditional practices that focus on pharmaceutical sales, extended community pharmacy services (ECPSs) are patient-centred and typically offered by specialised healthcare centres, which improve public health, reduce pressure imposed on healthcare professionals, and rationalise health system expenditures. However, based on the findings of several studies, community pharmacies (CPs) only provide marginalised services. Public reviews are thus crucial to effectively utilise such services. This study explored CPs use among the Saudi public in terms of knowledge, attitudes, and barriers to ECPSs. MATERIALS AND METHODS: We conducted a cross-sectional web-based survey of a non-probability sample between October and December 2021. Numerical and graphical descriptive statistics were employed with an additional analytical assessment using binary logistic regression to determine the association between participant characteristics and the barriers to ECPSs use. RESULTS: A total of 563 individuals participated in this study, approximately 33% of which revealed CPs as the first place they visit for medication concerns. Most individuals were not aware of medication therapy management and health screening services (77% and 68%, respectively). Pharmacy clinics offering private counselling and receiving patient electronic medical records were unknown to the participants (78% and 63%, respectively). A substantial proportion of the cohort considered lack of privacy (58%) and inadequate communication with community pharmacists (56%) as key barriers to the use of ECPSs. Logistic regression analysis revealed that the underdeveloped infrastructure of CPs was significantly associated with almost all factors. CONCLUSION: Most services and facilities were found to be underutilised. Positive public attitudes were associated with concerns regarding privacy and cost of services. Consistent with Saudi Vision 2030, supporting CPs and increasing the public awareness of ECPSs have significant implications on public health.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

National, regional, and global estimates of preterm birth in 2020, with trends from 2010: a systematic analysis.

BACKGROUND: Preterm birth is the leading cause of neonatal mortality and is associated with long-term physical, neurodevelopmental, and socioeconomic effects. This study updated national preterm birth rates and trends, plus novel estimates by gestational age subgroups, to inform progress towards global health goals and targets, and aimed to update country, regional, and global estimates of preterm birth for 2020 in addition to trends between 2010 and 2020. METHODS: We systematically searched population-based, nationally representative data on preterm birth from Jan 1, 2010, to Dec 31, 2020 and study data (26 March-14 April, 2021) for countries and areas with no national-level data. The analysis included 679 data points (86% nationally representative administrative data [582 of 679 data points]) from 103 countries and areas (62% of countries and areas having nationally representative administrative data [64 of 103 data points]). A Bayesian hierarchical regression was used for estimating country-level preterm rates, which incoporated country-specific intercepts, low birthweight as a covariate, non-linear time trends, and bias adjustments based on a data quality categorisation, and other indicators such as method of gestational age estimation. FINDINGS: An estimated 13·4 million (95% credible interval [CrI] 12·3-15·2 million) newborn babies were born preterm (<37 weeks) in 2020 (9·9% of all births [95% CrI 9·1-11·2]) compared with 13·8 million (12·7-15·5 million) in 2010 (9·8% of all births [9·0-11·0]) worldwide. The global annual rate of reduction was estimated at -0·14% from 2010 to 2020. In total, 55·6% of total livebirths are in southern Asia (26·8% [36 099 000 of 134 767 000]) and sub-Saharan Africa (28·7% [38 819 300 of 134 767 000]), yet these two regions accounted for approximately 65% (8 692 000 of 13 376 200) of all preterm births globally in 2020. Of the 33 countries and areas in the highest data quality category, none were in southern Asia or sub-Saharan Africa compared with 94% (30 of 32 countries) in high-income countries and areas. Worldwide from 2010 to 2020, approximately 15% of all preterm births occurred at less than 32 weeks of gestation, requiring more neonatal care (<28 weeks: 4·2%, 95% CI 3·1-5·0, 567 800 [410 200-663 200 newborn babies]); 28-32 weeks: 10·4% [9·5-10·6], 1 392 500 [1 274 800-1 422 600 newborn babies]). INTERPRETATION: There has been no measurable change in preterm birth rates over the last decade at global level. Despite increasing facility birth rates and substantial focus on routine health data systems, there remain many missed opportunities to improve preterm birth data. Gaps in national routine data for preterm birth are most marked in regions of southern Asia and sub-Saharan Africa, which also have the highest estimated burden of preterm births. Countries need to prioritise programmatic investments to prevent preterm birth and to ensure evidence-based quality care when preterm birth occurs. Investments in improving data quality are crucial so that preterm birth data can be improved and used for action and accountability processes. FUNDING: The Children's Investment Fund Foundation and the UNDP, United Nations Population Fund-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction.

Early warning and response system for dengue outbreaks: Moving from research to operational implementation in Mexico.

Dengue disease epidemics have increased in time and space due to climatic and non-climatic factors such as urbanization. In the absence of an effective vaccine, preventing dengue outbreak relies on vector control activities. Employing computerized tools to predict outbreaks and respond in advance has great potential for improving dengue disease control. Evidence of integrating or implementing such applications into control programs and their impact are scarce, and endemic countries demand for experience sharing and know-how transfer. Mexico has extensive experience of pre-validated EWARS (Early Warning And Response System), a tool that was developed in 2012 as part of a collaboration with the Special Program for Research and Training in Tropical Diseases Unit (TDR) at the World Health Organization and used at national level. The advancement of EWARS since 2014 and its stepwise integration into the national surveillance system has increased the appreciation of the need for integrated surveillance (including disease, vector and climate surveillance), and for linking inter-institutional and trans-sectoral information for holistic epidemiological intelligence. The integration of the EWARS software into the national surveillance platform in Mexico was a remarkable milestone and a successful experience. This manuscript describes the implementation process of EWARS in Mexico, which started in 2012 and further demonstrates benefits, threats, and opportunities of integrating EWARS into existing national surveillance programs.

Factors associated with time to first dialysis-associated peritonitis episode: Data from the Peritonitis Prevention Study (PEPS).

INTRODUCTION: Peritonitis remains a potentially serious complication of peritoneal dialysis (PD) treatment. It is therefore important to identify risk factors in order to reduce the incidence of peritonitis. The aim of the present analysis was to identify factors associated with time to first peritonitis episode. METHODS: Incident PD patients from 57 centres in Europe participated in the prospective randomised controlled Peritonitis Prevention Study (PEPS) from 2010 to 2015. Peritonitis-free, self-care PD patients ≥18 years were randomised to a retraining or a control group and followed for 1-36 months after PD initiation. The association of biochemical, clinical and prescription data with time to first peritonitis episode was studied. RESULTS: A first peritonitis episode was experienced by 33% (223/671) of participants. Univariable Cox proportional hazard regression showed a strong association between the time-updated number of PD bags connected per 24 h (PD bags/24 h) and time to first peritonitis episode (HR 1.35; 95% confidence interval (CI) 1.17-1.57), even after inclusion of PD modalities in the same model. Multivariable Cox regression revealed that the factors independently associated with time to first peritonitis episode included age (HR 1.16 per 10 years; 95% CI 1.05-1.28), PD bags/24 h (HR 1.32; 95% CI 1.13-1.54), serum albumin <35 versus >35 g/L (HR 1.39; 95% CI 1.06-1.82) and body weight per 10 kg (HR 1.10; 95% CI 1.01-1.19). CONCLUSION: This study of incident PD patients indicates that older age, greater number of PD bags connected/24 h, higher body weight and hypoalbuminaemia are independently associated with a shorter time to first peritonitis episode.

Patterns and contextual determinants of antibiotic prescribing for febrile under-five outpatients at primary and secondary healthcare facilities in Bugisu, Eastern Uganda.

Objectives: To describe patterns and contextual determinants of antibiotic prescribing for febrile under-five outpatients at primary and secondary healthcare facilities across Bugisu, Eastern Uganda. Methods: We surveyed 37 public and private-not-for-profit healthcare facilities and conducted a retrospective review of antimicrobial prescribing patterns among febrile under-five outpatients (with a focus on antibiotics) in 2019-20, based on outpatient registers. Multilevel logistic regression analysis was used to identify determinants of antibiotic prescribing at patient- and healthcare facility-levels. Results: Antibiotics were prescribed for 62.2% of 3471 febrile under-five outpatients. There were a total of 2478 antibiotic prescriptions of 22 antibiotic types: amoxicillin (52.2%), co-trimoxazole (14.7%), metronidazole (6.9%), gentamicin (5.7%), ceftriaxone (5.3%), ampicillin/cloxacillin (3.6%), penicillin (3.1%), and others (8.6%). Acute upper respiratory tract infection (AURTI) was the commonest single indication for antibiotic prescribing, with 76.3% of children having AURTI as their only documented diagnosis receiving antibiotic prescriptions. Only 9.2% of children aged 2-59 months with non-severe pneumonia received antibiotic prescriptions in line with national guidelines. Higher health centre levels, and private-not-for-profit ownership (adjusted OR, 4.30; 95% CI, 1.91-9.72) were significant contextual determinants of antibiotic prescribing. Conclusions: We demonstrated a high antibiotic prescribing prevalence among febrile under-five outpatients in Bugisu, Eastern Uganda, including prescriptions for co-trimoxazole and ampicillin/cloxacillin (which are not indicated in the management of the common causes of under-five febrile illness in Uganda). Study findings may be linked to limited diagnostic capacity and inadequate antibiotic availability, which require prioritization in interventions aimed at improving rational antibiotic prescribing among febrile under-five outpatients.

The Early Warning and Response System (EWARS-TDR) for dengue outbreaks: can it also be applied to chikungunya and Zika outbreak warning?

BACKGROUND: In the Americas, endemic countries for Aedes-borne diseases such as dengue, chikungunya, and Zika face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vectors Aedes aegypti and Ae. albopictus. The Special Program for Research and Training in Tropical Diseases (TDR-WHO) has developed together with partners an Early Warning and Response System (EWARS) for dengue outbreaks based on a variety of alarm signals with a high sensitivity and positive predictive value (PPV). The question is if this tool can also be used for the prediction of Zika and chikungunya outbreaks. METHODOLOGY: We conducted in nine districts of Mexico and one large city in Colombia a retrospective analysis of epidemiological data (for the outbreak definition) and of climate and entomological data (as potential alarm indicators) produced by the national surveillance systems for dengue, chikungunya and Zika outbreak prediction covering the following outbreak years: for dengue 2012-2016, for Zika 2015-2017, for chikungunya 2014-2016. This period was divided into a "run in period" (to establish the "historical" pattern of the disease) and an "analysis period" (to identify sensitivity and PPV of outbreak prediction). RESULTS: In Mexico, the sensitivity of alarm signals for correctly predicting an outbreak was 100% for dengue, and 97% for Zika (chikungunya data could not be obtained in Mexico); the PPV was 83% for dengue and 100% for Zika. The time period between alarm and start of the outbreak (i.e. the time available for early response activities) was for Zika 4-5 weeks. In Colombia the sensitivity of the outbreak prediction was 92% for dengue, 93% for chikungunya and 100% for Zika; the PPV was 68% for dengue, 92% for chikungunya and 54% for Zika; the prediction distance was for dengue 3-5 weeks, for chikungunya 10-13 weeks and for Zika 6-10 weeks. CONCLUSION: EWARS demonstrated promising capability of timely disease outbreak prediction with an operational design likely to improve the coordination among stakeholders. However, the prediction validity varied substantially across different types of diseases and appeared less optimal in low endemic settings.

The Impact of Occupational Noise Exposure on Hyperacusis: a Longitudinal Population Study of Female Workers in Sweden.

OBJECTIVES: The aim was to assess the risk of hyperacusis in relation to occupational noise exposure among female workers in general, and among women working in preschool specifically. DESIGN: A retrospective longitudinal study was performed. Survey data were collected in 2013 and 2014 from two cohorts: randomly selected women from the population in region Västra Götaland, Sweden, and women selected based on having received a preschool teacher degree from universities in the same region. The final study sample included n = 8328 women born between 1948 and 1989. Occupational noise exposure was objectively assigned to all time periods from the first to the last reported occupation throughout working life, using the Swedish Job-Exposure Matrix (JEM) with three exposure intervals: <75 dB(A), 75 to 85 dB(A), and >85 dB(A). The JEM assigns preschool teachers to the 75 to 85 dB(A) exposure interval. The outcome hyperacusis was assessed by self-report using one question addressing discomfort or pain from everyday sounds. In the main analysis, a hyperacusis event was defined by the reported year of onset, if reported to occur at least a few times each week. Additional sensitivity analyses were performed using more strict definitions: (a) at least several times each week and (b) every day. The risk (hazard ratio, HR) of hyperacusis was analyzed in relation to years of occupational noise exposure, using survival analysis with frailty regression modeling accounting for individual variation in survival times which reflect, for example, noise exposure during years prior to onset. Occupational noise exposure was defined by the occupation held at year of hyperacusis onset, or the occupation held at the survey year if no event occurred. Models were adjusted for confounders including age, education, income, family history of hearing loss, and change of jobs due to noise. RESULTS: In total, n = 1966 hyperacusis events between 1960 and 2014 were analyzed in the main analysis. A significantly increased risk of hyperacusis was found among women working in any occupation assigned to the 75 to 85 dB(A) noise exposure group [HR: 2.6, 95% confidence interval (CI): 2.4-2.9], compared with the reference group <75 dB(A). The risk was tripled among preschool teachers specifically (HR: 3.4, 95% CI: 3.0-3.7), with the crude Kaplan-Meier curve showing a higher rate of onset early in the working life in preschool teachers compared with all the other exposure groups. The risk was increased, but not statistically significant in the main analysis, for the highest exposure group >85 dB(A), where only six hyperacusis events were identified (HR: 1.4, 95% CI: 0.6-3.1). In the sensitivity analysis, where hyperacusis was defined as occurring every day, the HR was significant also in the highest exposure group (HR: 3.8, 95% CI: 1.4-10.3), and generally slightly higher in the other exposure groups compared to the main analysis. CONCLUSIONS: This study indicates increased risk of hyperacusis already below the permissible occupational noise exposure limit in Sweden (85 dB LAeq,8h) among female workers in general, and in particular among preschool teachers. Prospective studies and less wide exposure intervals could confirm causal effects and assess dose-response relationships, respectively, although this study at present suggest a need for risk assessment, improved hearing prevention measures, and noise abatement measures in occupations with noise levels from 75 dB(A). The results could also have implications for management of occupational disability claims.

Waterpipe Tobacco Smoking and Other Multiple Sclerosis Environmental Risk Factors.

INTRODUCTION: There are a number of well-established risk factors for multiple sclerosis (MS). Other factors, however, showed conflicting or inconsistent results. Here, we examine some factors that are unique to or more practiced in Saudi Arabia (SA) and the Arab region such as waterpipe tobacco smoking (WTS), face veiling, raw milk (RM) and camel milk (CM) consumption, and tuberculosis (TB) infection in addition to other traditional factors. METHODS: This is a sex- and age-matched case-control study in which we used a structured questionnaire to examine the relation between a number of factors and exposures and the risk of MS. Three hundred MS patients and 601 controls were included. Data were analyzed across different statistical models using logistic regression adjusting for age, sex, marital status, duration of breastfeeding, age first joining school, coffee consumption, and face exposure. RESULTS: Cigarette smoking (OR = 1.79, [95% CI: 1.01-3.17], p = 0.047), WTS (OR = 2.25, [95% CI: 1.21-4.15], p = 0.010), and CM consumption (OR = 2.50, [95% CI: 1.20-5.21], p = 0.014) increased the risk of MS, while performing hajj (OR = 0.47, [95% CI: 0.34-0.67], p = 0.001), TB infection (OR = 0.29, [95% CI: 0.11-0.78], p = 0.015), face veiling (OR = 0.32, [95% CI: 0.23-0.47], p = 0.001), and coffee consumption (OR = 0.67, [95% CI: 0.49-0.89], p = 0.008) appeared to be associated with decreased risk. No association was found between fast food, processed meat, soft drinks, animal milk (other than camel), or RM consumption and the risk of MS. CONCLUSION: The results of this case-control study confirm that different means of tobacco smoking are associated with increased risk of MS. It also sheds more light on the complex association between infections and MS.

Validation of the Early Warning and Response System (EWARS) for dengue outbreaks: Evidence from the national vector control program in Mexico.

BACKGROUND: During 2017, twenty health districts (locations) implemented a dengue outbreak Early Warning and Response System (EWARS) in Mexico, which processes epidemiological, meteorological and entomological alarm indicators to predict dengue outbreaks and triggers early response activities. Out of the 20 priority districts where more than one fifth of all national disease transmission in Mexico occur, eleven districts were purposely selected and analyzed. Nine districts presented outbreak alarms by EWARS but without subsequent outbreaks ("non-outbreak districts") and two presented alarms with subsequent dengue outbreaks ("outbreak districts"). This evaluation study assesses and compares the impact of alarm-informed response activities and the consequences of failing a timely and adequate response across the outbreak groups. METHODS: Five indicators of dengue outbreak response (larval control, entomological studies with water container interventions, focal spraying and indoor residual spraying) were quantitatively analyzed across two groups ("outbreak districts" and "non-outbreak districts"). However, for quality control purposes, only qualitative concluding remarks were derived from the fifth response indicator (fogging). RESULTS: The average coverage of vector control responses was significantly higher in non-outbreak districts and across all four indicators. In the "outbreak districts" the response activities started late and were of much lower intensity compared to "non-outbreak districts". Vector control teams at districts-level demonstrated diverse levels of compliance with local guidelines for 'initial', 'early' and 'late' responses to outbreak alarms, which could potentially explain the different outcomes observed following the outbreak alarms. CONCLUSION: Failing timely and adequate response of alarm signals generated by EWARS showed to negatively impact the disease outbreak control process. On the other hand, districts with adequate and timely response guided by alarm signals demonstrated successful records of outbreak prevention. This study presents important operational scenarios when failing or successding EWARS but warrants investigating the effectiveness and cost-effectiveness of EWARS using a more robust designs.

Study protocol for WHO and UNICEF estimates of global, regional, and national preterm birth rates for 2010 to 2019.

BACKGROUND: Preterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019. METHODS: Preterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman's last menstrual period. National administrative data sources for WHO Member States with facility birth rates of ≥80% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if ≥80% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model. DISCUSSION: Accurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality. TRIAL REGISTRATION: PROSPERO registration: CRD42021237861.

Factors shaping the COVID-19 epidemic curve: a multi-country analysis.

BACKGROUND: Lockdown measures are the backbone of containment measures for the COVID-19 pandemic both in high-income countries (HICs) and low- and middle-income countries (LMICs). However, in view of the inevitably-occurring second and third global covid-19 wave, assessing the success and impact of containment measures on the epidemic curve of COVID-19 and people's compliance with such measures is crucial for more effective policies. To determine the containment measures influencing the COVID-19 epidemic curve in nine targeted countries across high-, middle-, and low-income nations. METHODS: Four HICs (Germany, Sweden, Italy, and South Korea) and five LMICs (Mexico, Colombia, India, Nigeria, and Nepal) were selected to assess the association using interrupted time series analysis of daily case numbers and deaths of COVID-19 considering the following factors: The "stringency index (SI)" indicating how tight the containment measures were implemented in each country; and the level of compliance with the prescribed measures using human mobility data. Additionally, a scoping review was conducted to contextualize the findings. RESULTS: Most countries implemented quite rigorous lockdown measures, particularly the LMICs (India, Nepal, and Colombia) following the model of HICs (Germany and Italy). Exceptions were Sweden and South Korea, which opted for different strategies. The compliance with the restrictions-measured as mobility related to home office, restraining from leisure activities, non-use of local transport and others-was generally good, except in Sweden and South Korea where the restrictions were limited. The endemic curves and time-series analysis showed that the containment measures were successful in HICs but not in LMICs. CONCLUSION: The imposed lockdown measures are alarming, particularly in resource-constrained settings where such measures are independent of the population segment, which drives the virus transmission. Methods for examining people's movements or hardships that are caused by covid- no work, no food situation are inequitable. Novel and context-adapted approach of dealing with the COVID-19 crisis are therefore crucial.

Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review.

BACKGROUND: Early warning systems (EWSs) are of increasing importance in the context of outbreak-prone diseases such as chikungunya, dengue, malaria, yellow fever, and Zika. A scoping review has been undertaken for all 5 diseases to summarize existing evidence of EWS tools in terms of their structural and statistical designs, feasibility of integration and implementation into national surveillance programs, and the users' perspective of their applications. METHODS: Data were extracted from Cochrane Database of Systematic Reviews (CDSR), Google Scholar, Latin American and Caribbean Health Sciences Literature (LILACS), PubMed, Web of Science, and WHO Library Database (WHOLIS) databases until August 2019. Included were studies reporting on (a) experiences with existing EWS, including implemented tools; and (b) the development or implementation of EWS in a particular setting. No restrictions were applied regarding year of publication, language or geographical area. FINDINGS: Through the first screening, 11,710 documents for dengue, 2,757 for Zika, 2,706 for chikungunya, 24,611 for malaria, and 4,963 for yellow fever were identified. After applying the selection criteria, a total of 37 studies were included in this review. Key findings were the following: (1) a large number of studies showed the quality performance of their prediction models but except for dengue outbreaks, only few presented statistical prediction validity of EWS; (2) while entomological, epidemiological, and social media alarm indicators are potentially useful for outbreak warning, almost all studies focus primarily or exclusively on meteorological indicators, which tends to limit the prediction capacity; (3) no assessment of the integration of the EWS into a routine surveillance system could be found, and only few studies addressed the users' perspective of the tool; (4) almost all EWS tools require highly skilled users with advanced statistics; and (5) spatial prediction remains a limitation with no tool currently able to map high transmission areas at small spatial level. CONCLUSIONS: In view of the escalating infectious diseases as global threats, gaps and challenges are significantly present within the EWS applications. While some advanced EWS showed high prediction abilities, the scarcity of tool assessments in terms of integration into existing national surveillance systems as well as of the feasibility of transforming model outputs into local vector control or action plans tends to limit in most cases the support of countries in controlling disease outbreaks.

Current smoking alters phospholipid- and surfactant protein A levels in small airway lining fluid: An explorative study on exhaled breath.

Small airways are difficult to access. Exhaled droplets, also referred to as particles, provide a sample of small airway lining fluid and may reflect inflammatory responses. We aimed to explore the effect of smoking on the composition and number of exhaled particles in a smoker-enriched study population. We collected and chemically analyzed exhaled particles from 102 subjects (29 never smokers, 36 former smokers and 37 current smokers) aged 39 to 83 years (median 63). A breathing maneuver maximized the number exhaled particles, which were quantified with a particle counter. The contents of surfactant protein A and albumin in exhaled particles was quantified with immunoassays and the contents of the phospholipids dipalmitoyl- and palmitoyl-oleoyl- phosphatidylcholine with mass spectrometry. Subjects also performed spirometry and nitrogen single breath washout. Associations between smoking status and the distribution of contents in exhaled particles and particle number concentration were tested with quantile regression, after adjusting for potential confounders. Current smokers, compared to never smokers, had higher number exhaled particles and more surfactant protein A in the particles. The magnitude of the effects of current smoking varied along the distribution of each PEx-variable. Among subjects with normal lung function, phospholipid levels were elevated in current smokers, in comparison to no effect of smoking on these lipids at abnormal lung function. Smoking increased exhaled number of particles and the contents of lipids and surfactant protein A in the particles. These findings might reflect early inflammatory responses to smoking in small airway lining fluid, also when lung function is within normal limits.

Swedish intrauterine growth reference ranges for estimated fetal weight.

Fetal growth restriction is a strong risk factor for perinatal morbidity and mortality. Reliable standards are indispensable, both to assess fetal growth and to evaluate birthweight and early postnatal growth in infants born preterm. The aim of this study was to create updated Swedish reference ranges for estimated fetal weight (EFW) from gestational week 12-42. This prospective longitudinal multicentre study included 583 women without known conditions causing aberrant fetal growth. Each woman was assigned a randomly selected protocol of five ultrasound scans from gestational week 12 + 3 to 41 + 6. Hadlock's 3rd formula was used to estimate fetal weight. A two-level hierarchical regression model was employed to calculate the expected median and variance, expressed in standard deviations and percentiles, for EFW. EFW was higher for males than females. The reference ranges were compared with the presently used Swedish, and international reference ranges. Our reference ranges had higher EFW than the presently used Swedish reference ranges from gestational week 33, and higher median, 2.5th and 97.5th percentiles from gestational week 24 compared with INTERGROWTH-21st. The new reference ranges can be used both for assessment of intrauterine fetal weight and growth, and early postnatal growth in children born preterm.