Conceptual hydrological model calibration using multi-objective optimization techniques over the transboundary Komadugu-Yobe basin, Lake Chad Area, West Africa

Study Area: The discharge of the transboundary Komadugu-Yobe Basin, Lake Chad Area, West Africa is calibrated using multi-objective optimization techniques. Study focus: The GR5J hydrological model parameters are calibrated using six optimization methods i.e. Local Optimization-Multi Start (LOMS), the Differential Evolution (DE), the Multiobjective Particle the Swarm Optimization (MPSO), the Memetic Algorithm with Local Search Chains (MALS), the Shuffled Complex Evolution-Rosenbrock’s function (SCE-R), and the Bayesian Markov Chain Monte Carlo (MCMC) approach. Three combined objective functions i.e. Root Mean Square Error, Nash- Sutcliffe efficiency, Kling-Gupta efficiency are applied. The calibration process is divided into two separate episodes (1974–2000 and 1980–1995) so as to ascertain the robustness of the calibration approaches. Runoff simulation results are analysed with a timefrequency wavelet transform. New hydrological insights for the region: For calibration and validation stages, all optimization methods simulate the base flow and high flow spells with a satisfactory level of accuracy. For calibration period, MCMC underestimate it by -0.07 mm/day. The performance evaluation shows that MCMC has the highest values of mean absolute error (0.28) and mean square error (0.40) while LOMS and MCMC record a low volumetric efficiency of 0.56. In all cases, the DE and the SCE-R methods perform better than others. The combination of multi-objective functions and multi-optimization techniques improve the model’s parameters stability and the algorithms’ optimization to represent the runoff in the basin

Chronic airflow obstruction and ambient particulate air pollution

Smoking is the most well-established cause of chronic airflow obstruction (CAO) but particulate air pollution and poverty have also been implicated. We regressed sex-specific prevalence of CAO from 41 Burden of Obstructive Lung Disease study sites against smoking prevalence from the same study, the gross national income per capita and the local annual mean level of ambient particulate matter (PM2.5) using negative binomial regression. The prevalence of CAO was not independently associated with PM2.5 but was strongly associated with smoking and was also associated with poverty. Strengthening tobacco control and improved understanding of the link between CAO and poverty should be prioritised

Essential Medicines at the National Level : The Global Asthma Network's Essential Asthma Medicines Survey 2014

Patients with asthma need uninterrupted supplies of affordable, quality-assured essential medicines. However, access in many low- and middle-income countries (LMICs) is limited. The World Health Organization (WHO) Non-Communicable Disease (NCD) Global Action Plan 2013-2020 sets an 80% target for essential NCD medicines' availability. Poor access is partly due to medicines not being included on the national Essential Medicines Lists (EML) and/or National Reimbursement Lists (NRL) which guide the provision of free/subsidised medicines. We aimed to determine how many countries have essential asthma medicines on their EML and NRL, which essential asthma medicines, and whether surveys might monitor progress. A cross-sectional survey in 2013-2015 of Global Asthma Network principal investigators generated 111/120 (93%) responses41 high-income countries and territories (HICs); 70 LMICs. Patients in HICs with NRL are best served (91% HICs included ICS (inhaled corticosteroids) and salbutamol). Patients in the 24 (34%) LMICs with no NRL and the 14 (30%) LMICs with an NRL, however no ICS are likely to have very poor access to affordable, quality-assured ICS. Many LMICs do not have essential asthma medicines on their EML or NRL. Technical guidance and advocacy for policy change is required. Improving access to these medicines will improve the health system's capacity to address NCDs.Peer reviewe

Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

Cohort Profile: Burden of Obstructive Lung Disease (BOLD) study

The Burden of Obstructive Lung Disease (BOLD) study was established to assess the prevalence of chronic airflow obstruction, a key characteristic of chronic obstructive pulmonary disease, and its risk factors in adults (≥40 years) from general populations across the world. The baseline study was conducted between 2003 and 2016, in 41 sites across Africa, Asia, Europe, North America, the Caribbean and Oceania, and collected high-quality pre- and post-bronchodilator spirometry from 28 828 participants. The follow-up study was conducted between 2019 and 2021, in 18 sites across Africa, Asia, Europe and the Caribbean. At baseline, there were in these sites 12 502 participants with high-quality spirometry. A total of 6452 were followed up, with 5936 completing the study core questionnaire. Of these, 4044 also provided high-quality pre- and post-bronchodilator spirometry. On both occasions, the core questionnaire covered information on respiratory symptoms, doctor diagnoses, health care use, medication use and ealth status, as well as potential risk factors. Information on occupation, environmental exposures and diet was also collected

Analysis of climate extreme indices over the Komadugu-Yobe basin, Lake Chad region: past and future occurrences

This study investigates trends of climate extreme indices in the Komadugu-Yobe Basin (KYB) based on observed data of the period 1971–2017 as well as regional climate model (RCM) simulations for the historical period (1979–2005), the near future (2020–2050), and the far future (2060–2090). In order to correct change points in the time historical series, the Adapted Caussinus Mestre Algorithm for homogenising Networks of Temperature series homogeneity test is used. The magnitude of the linear trends is estimated using the Sen's slope estimator and Mann-Kendall's test is performed to check the statistical significance of the trends. Future trends are assessed using the ensemble mean of eight regional climate model data under two emission scenarios, provided by the Coordinated Regional Climate Downscaling Experiment (CORDEX). Therefore, the projected rainfall and temperature have been corrected for biases by using empirical Quantile Mapping. In the observations, warm spell duration, warm day-, and warm night frequencies exhibit statistically significant positive trends. Although there is a positive trend in the annual total rainfall, the number of consecutive wet (dry) days decreases (increases). The future climate also shows a continuing positive trend in the temperature extreme indices as well as more frequent extreme rainfall events. Therefore, it is pertinent for decision-makers to develop suitable adaptation and mitigating measures to combat climate change in the Basin. Keywords: Homogeneity, Climate extreme indices, Linear trends, Bias correction, Komadugu-Yobe basin, Lake Chad regio

Seasonal precipitation variability in regional climate simulations over Northern basins of Tunisia

Northern Tunisia is the rainiest part of the country where most of the water management structures (dams, reservoirs, etc) are located. Its strategic situation with respect to surface water resources encourages the investigation of the climate change impacts projected by climate models. The goal of this study is first to compare the observed precipitation with climate model outputs, and then to evaluate the future changes projected by different climate models. The study area is subdivided into four regions: the upstream and downstream transboundary Medjerda basin, the northern coastal basins and the eastern coastal basins. A database provided by the Tunisian hydrological service includes 388 stations with complete monthly precipitation data over the period 1961-2000. An ensemble of Regional Climate Models (RCM) simulations provided by the European Union-funded project ENSEMBLES are used. Six RCM model runs (CNR-A, DMI-A, DMI-B, ICT-E, SMH-B and SMH-E) are analysed, for the control period 1961-2000 and two projection periods, 2011-2050 and 2051-2090. The models efficiency in reproducing seasonal precipitation amounts and variability is evaluated. A 1-km monthly precipitation reference grid is computed through the interpolation of rainfall observations during the period 1961-2000 with kriging techniques. Monthly precipitation series averaged over the four basins are built for comparison during the control period. The RCM outputs are evaluated with respect to the annual precipitation cycle and rainfall frequency distribution using robust statistics. For the control period, features of the seasonal regimes are well reproduced by all models. It is found that models underestimate seasonal precipitation on average by 20%. The discrepancy between model outputs and observations depends on the season. For the future, in summer and autumn the different models do not project major changes in the seasonal distributions. However, for winter and spring, all the models project a significant decrease of precipitations