Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios

Associations between eight earth observation-derived climate variables and enteropathogen infection: An independent participant data meta-analysis of surveillance studies with broad spectrum nucleic acid diagnostics

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen‐specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens—adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter, ETEC, Shigella, Cryptosporidium and Giardia—was matched by date with hydrometeorological variables from a global Earth observation dataset—precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non‐linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7‐day average temperatures—a relative risk of 0.76 (95% confidence interval: 0.69–0.85) above 28°C—while ETEC risk increased by almost half, 1.43 (1.36–1.50), in the 20–35°C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species\u27 risk increased following lower‐than‐average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea‐causing agents as the global climate changes

Advanced Technologies for Oral Controlled Release: Cyclodextrins for oral controlled release

Cyclodextrins (CDs) are used in oral pharmaceutical formulations, by means of inclusion complexes formation, with the following advantages for the drugs: (1) solubility, dissolution rate, stability and bioavailability enhancement; (2) to modify the drug release site and/or time profile; and (3) to reduce or prevent gastrointestinal side effects and unpleasant smell or taste, to prevent drug-drug or drug-additive interactions, or even to convert oil and liquid drugs into microcrystalline or amorphous powders. A more recent trend focuses on the use of CDs as nanocarriers, a strategy that aims to design versatile delivery systems that can encapsulate drugs with better physicochemical properties for oral delivery. Thus, the aim of this work was to review the applications of the CDs and their hydrophilic derivatives on the solubility enhancement of poorly water soluble drugs in order to increase their dissolution rate and get immediate release, as well as their ability to control (to prolong or to delay) the release of drugs from solid dosage forms, either as complexes with the hydrophilic (e.g. as osmotic pumps) and/ or hydrophobic CDs. New controlled delivery systems based on nanotechonology carriers (nanoparticles and conjugates) have also been reviewed

Associations Between Eight Earth Observation-Derived Climate Variables and Enteropathogen Infection : An Independent Participant Data Meta-Analysis of Surveillance Studies With Broad Spectrum Nucleic Acid Diagnostics

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen-specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens-adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter, ETEC, Shigella, Cryptosporidium and Giardia-was matched by date with hydrometeorological variables from a global Earth observation dataset-precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non-linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7-day average temperatures-a relative risk of 0.76 (95% confidence interval: 0.69-0.85) above 28 degrees C-while ETEC risk increased by almost half, 1.43 (1.36-1.50), in the 20-35 degrees C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species' risk increased following lower-than-average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea-causing agents as the global climate changes. Plain Language Summary Diarrheal disease is a big health problem for children. It can be caused by different bugs, which can be caught more easily in certain weather conditions, though not much is understood about this because the climate varies so much from one place to the next. This study combined data from many different countries where diarrhea-causing bugs were diagnosed in children's stool. Satellites recorded what the weather was like on the day each sample was collected. Rotavirus is easiest to catch in cold weather and when water washes over the ground after rain. Dry weather also makes it and other viruses easy to catch. Bacteria spread best when the air is warm and humid, and the soil moist, though one type of E. coli can also be spread in rainwater. Climate change will make dry places drier, wet places wetter and everywhere warmer. This might lead to more diarrhea caused by bacteria and less by viruses in some places, though places with moist soil might see more of every kind of bug.Peer reviewe

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota.

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19

Spatiotemporal variation in risk of Shigella infection in childhood : a global risk mapping and prediction model using individual participant data

BACKGROUND: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and map its predicted prevalence across low-income and middle-income countries (LMICs). METHODS: Individual participant data for Shigella positivity in stool samples were sourced from multiple LMIC-based studies of children aged 59 months or younger. Covariates included household-level and participant-level factors ascertained by study investigators and environmental and hydrometeorological variables extracted from various data products at georeferenced child locations. Multivariate models were fitted and prevalence predictions obtained by syndrome and age stratum. FINDINGS: 20 studies from 23 countries (including locations in Central America and South America, sub-Saharan Africa, and south and southeast Asia) contributed 66 563 sample results. Age, symptom status, and study design contributed most to model performance followed by temperature, wind speed, relative humidity, and soil moisture. Probability of Shigella infection exceeded 20% when both precipitation and soil moisture were above average and had a 43% peak in uncomplicated diarrhoea cases at 33°C temperatures, above which it decreased. Compared with unimproved sanitation, improved sanitation decreased the odds of Shigella infection by 19% (odds ratio [OR]=0·81 [95% CI 0·76-0·86]) and open defecation decreased them by 18% (OR=0·82 [0·76-0·88]). INTERPRETATION: The distribution of Shigella is more sensitive to climatological factors, such as temperature, than previously recognised. Conditions in much of sub-Saharan Africa are particularly propitious for Shigella transmission, although hotspots also occur in South America and Central America, the Ganges-Brahmaputra Delta, and the island of New Guinea. These findings can inform prioritisation of populations for future vaccine trials and campaigns. FUNDING: NASA, National Institutes of Health-The National Institute of Allergy and Infectious Diseases, and Bill & Melinda Gates Foundation.publishedVersionPeer reviewe

Variation in postoperative outcomes of patients with intracranial tumors: insights from a prospective international cohort study during the COVID-19 pandemic

Background: This study assessed the international variation in surgical neuro-oncology practice and 30-day outcomes of patients who had surgery for an intracranial tumor during the COVID-19 pandemic. Methods: We prospectively included adults aged ≥18 years who underwent surgery for a malignant or benign intracranial tumor across 55 international hospitals from 26 countries. Each participating hospital recorded cases for 3 consecutive months from the start of the pandemic. We categorized patients’ location by World Bank income groups (high [HIC], upper-middle [UMIC], and low- and lower-middle [LLMIC]). Main outcomes were a change from routine management, SARS-CoV-2 infection, and 30-day mortality. We used a Bayesian multilevel logistic regression stratified by hospitals and adjusted for key confounders to estimate the association between income groups and mortality. Results: Among 1016 patients, the number of patients in each income group was 765 (75.3%) in HIC, 142 (14.0%) in UMIC, and 109 (10.7%) in LLMIC. The management of 200 (19.8%) patients changed from usual care, most commonly delayed surgery. Within 30 days after surgery, 14 (1.4%) patients had a COVID-19 diagnosis and 39 (3.8%) patients died. In the multivariable model, LLMIC was associated with increased mortality (odds ratio 2.83, 95% credible interval 1.37–5.74) compared to HIC. Conclusions: The first wave of the pandemic had a significant impact on surgical decision-making. While the incidence of SARS-CoV-2 infection within 30 days after surgery was low, there was a disparity in mortality between countries and this warrants further examination to identify any modifiable factors

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Applications of Climate Regionalization: Statistical Prediction and Patterns of Precipitation Variability in Observations and Global Climate Models

Rainfall in the tropical Africa is prone to large temporal and spatial variability. The well-documented social impacts of this variability have motivated numerous efforts at seasonal precipitation prediction, many of which employ statistical techniques that forecast precipitation as a function of large-scale climate indices. These statistical models have demonstrated some skill, but nearly all have adopted conventional statistical modeling techniques—most commonly generalized linear models—to associate predictor fields with precipitation anomalies. Here, a new approach is proposed to identify regional patterns of precipitation variability based on objective climate regionalization to understand the physical patterns and drivers of spatio-temporal variability in the regional scale as well as ties to global patterns. Then, advanced statistical models were applied to provide skillful predictions as well as to identify large-scale drivers and capture nonlinear influences that multiple major modes of variability have on each region. This raises questions regarding the spatial extent and regional connectivity of changes inferred from observations, proxies, and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, Hierarchical Climate Regionalization (HiClimR) package in R was developed and applied to regionalize Africa using observations and Global Climate Model (GCM) historical simulations and future projections. HiClimR was utilized for the regionalization of Africa based on interannual precipitation variability using monthly Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) data for the period 1981-2014. A number of data processing techniques and clustering algorithms were tested in order to ensure a robust definition of climate regions. The final regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions were then compared to those of five GCMs for the historic period. Focusing on boreal summer, we note key similarities and differences between CHIRPS and GCMs, including discussion of the coherence of the Sahel in observation and some, but not all, models. This serves as a basis for examining the representation of teleconnections in GCMs relative to observations. It also provides a foundation for interpreting GCM results in cases where the model’s climate regions do not align with observation. Finally, we examine shifts in climate regions under projected 21st century climate change for different GCMs and emissions pathways. We note a projected change in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high emissions scenarios

Flash drought onset over the contiguous United States: sensitivity of inventories and trends to quantitative definitions

The term “flash drought” is frequently invoked to describe droughts that develop rapidly over a relatively short timescale. Despite extensive and growing research on flash drought processes, predictability, and trends, there is still no standard quantitative definition that encompasses all flash drought characteristics and pathways. Instead, diverse definitions have been proposed, supporting wide-ranging studies of flash drought but creating the potential for confusion as to what the term means and how to characterize it. Use of different definitions might also lead to different conclusions regarding flash drought frequency, predictability, and trends under climate change. In this study, we compared five previously published definitions, a newly proposed definition, and an operational satellite-based drought monitoring product to clarify conceptual differences and to investigate the sensitivity of flash drought inventories and trends to the choice of definition. Our analyses indicate that the newly introduced Soil Moisture Volatility Index definition effectively captures flash drought onset in both humid and semi-arid regions. Analyses also showed that estimates of flash drought frequency, spatial distribution, and seasonality vary across the contiguous United States depending upon which definition is used. Definitions differ in their representation of some of the largest and most widely studied flash droughts of recent years. Trend analysis indicates that definitions that include air temperature show significant increases in flash droughts over the past 40 years, but few trends are evident for definitions based on other surface conditions or fluxes. These results indicate that “flash drought” is a composite term that includes several types of events and that clarity in definition is critical when monitoring, forecasting, or projecting the drought phenomenon