BackgroundMalaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region.MethodsThis study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models.ResultsTwo models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts.ConclusionResults indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1602-1) contains supplementary material, which is available to authorized users.

Subject to a high burden of diarrheal diseases, Afghanistan is also susceptible to climate change. This study investigated the spatiotemporal distribution of diarrheal disease in the country and how associated it is with climate variables. Using monthly aggregated new cases of acute diarrhea reported between 2010 and 2016 and monthly averaged climate data at the district level, we fitted a hierarchical Bayesian spatiotemporal statistical model. We found aridity and mean daily temperature were positively associated with diarrhea incidence; every 1°C increase in mean daily temperature and 0.01-unit change in the aridity index were associated with a 0.70% (CI: 0.67%, 0.73%) increase and a 4.79% (CI: 4.30%, 5.26%) increase in the risk of diarrhea, respectively. Average annual temperature, on the other hand, was negatively associated, with a 3.7% (CI: 3.74%, 3.68) decrease in risk for every degree Celsius increase in annual average temperature. Temporally, most districts exhibited similar seasonal trends, with incidence peaking in summer, except for the eastern region where differences in climate patterns and population density may be associated with high rates of diarrhea throughout the year. The results from this study highlight the significant role of climate in shaping diarrheal patterns in Afghanistan, allowing policymakers to account for potential impacts of climate change in their public health assessments.

STUDY QUESTION Is increased alcohol intake in different phases of the menstrual cycle associated with fecundability in women? SUMMARY ANSWER Heavy intake (>6 drinks/week) of alcoholic beverages in the luteal phase and ovulatory subphase was associated with reduced odds of conception; moderate intake (3–6 drinks/week) during the luteal phase was also associated with reduced fecundability. WHAT IS KNOWN ALREADY Despite strong indications for increased risk of infertility among drinking women with intention to conceive, inconsistencies in previous results point to possible residual confounding, and have not thoroughly investigated timing of drinking and other drinking patterns during the menstrual cycle. STUDY DESIGN, SIZE, DURATION Participants in The Mount Sinai Study of Women Office Workers (MSSWOW), a prospective cohort study of fertility, were recruited and followed between 1990 and 1994, and completed daily diaries reporting their alcohol intake (type and number of drinks) for a maximum of 19 months of follow-up (N = 413). PARTICIPANTS/MATERIALS, SETTING, METHODS Participants were between 19 and 41 years of age. After completion of baseline surveys, they were asked to record their alcoholic beverage intake as number of drinks of beer, wine, and liquor per day, in addition to other exposures such as caffeine and smoking. Furthermore, they submitted urine samples each month to assess pregnancy. Menstrual cycle phases were calculated using the Knaus–Ognio approach. Discrete survival analysis methods were employed to estimate the association between categories of alcohol intake in each phase of menstrual cycle and fecundability. MAIN RESULTS AND THE ROLE OF CHANCE In the luteal phase, both moderate drinking (3–6 drinks/week, Fecundability Odds Ratio (FOR)=0.56, CI: 0.31, 0.98) and heavy drinking (>6 drinks/week, FOR = 0.51, CI: 0.29, 0.89) were associated with a reduction in fecundability, compared to non-drinkers. For the follicular phase, heavy drinking in the ovulatory sub-phase (FOR = 0.39, CI: 0.19, 0.72) was similarly associated with reduced fecundability, compared to non-drinkers. For the pre-ovulatory sub-phase, heavy drinking (>6 drinks/week, FOR = 0.54, CI: 0.29, 0.97) was associated with reduction in fecundability, but this association was inconsistent when subjected to sensitivity tests. Each extra day of binge drinking was associated with 19% (FOR = 0.81, CI: 0.63, 0.98), and 41% (FOR = 0.59, CI: 0.33, 0.93) reduction in fecundability for the luteal phase and ovulatory sub-phase respectively, but no association was observed in the pre-ovulatory sub-phase. No meaningful differences in fecundability between beverages were observed in any menstrual phase. LIMITATIONS, REASONS FOR CAUTION Patterns of alcohol intake in this cohort suggest a lower average alcohol intake compared to more recent national averages for the same demographic group. Sample sizes were small for some subgroups, resulting in limited power to examine specific beverage types in different phases of the menstrual cycle, or to assess interaction. In addition, the influence of male partner alcohol intake was not assessed, the data relied on self-report, and residual confounding (e.g. unmeasured behaviors correlated with alcohol intake) is a possibility. WIDER IMPLICATIONS OF THE FINDINGS Results suggest an inverse association between alcohol and fecundability, and support the relevance of menstrual cycle phases in this link. More specifically, moderate to heavy drinking during the luteal phase, and heavy drinking in the ovulatory window, could disturb the delicate sequence of hormonal events, affecting chances of a successful conception. STUDY FUNDING/COMPETING INTEREST(S) Authors declare no conflict of interest. This work was supported by the National Institutes of Health grant, R01-HD24618. TRIAL REGISTRATION NUMBER N/A

Background African ancestry individuals with comparable overall anthropometric measures to Europeans have lower abdominal adiposity. To explore the genetic underpinning of different adiposity patterns, we investigated whether genetic risk scores for well-studied adiposity phenotypes like body mass index (BMI) and waist circumference (WC) also predict other, less commonly measured adiposity measures in 2420 African American individuals from the Jackson Heart Study. Methods Polygenic risk scores (PRS) were calculated using GWAS-significant variants extracted from published studies mostly representing European ancestry populations for BMI, waist-hip ratio (WHR) adjusted for BMI (WHRBMIadj), waist circumference adjusted for BMI (WCBMIadj), and body fat percentage (BF%). Associations between each PRS and adiposity measures including BF%, subcutaneous adiposity tissue (SAT), visceral adiposity tissue (VAT) and VAT:SAT ratio (VSR) were examined using multivariable linear regression, with or without BMI adjustment. Results In non-BMI adjusted models, all phenotype-PRS were found to be positive predictors of BF%, SAT and VAT. WHR-PRS was a positive predictor of VSR, but BF% and BMI-PRS were negative predictors of VSR. After adjusting for BMI, WHR-PRS remained a positive predictor of BF%, VAT and VSR but not SAT. WC-PRS was a positive predictor of SAT and VAT; BF%-PRS was a positive predictor of BF% and SAT only. Conclusion These analyses suggest that genetically driven increases in BF% strongly associate with subcutaneous rather than visceral adiposity and BF% is strongly associated with BMI but not central adiposity-associated genetic variants. How common genetic variants may contribute to observed differences in adiposity patterns between African and European ancestry individuals requires further study.

This study reviewed trends in the incidence of common communicable diseases among children under five years in Afghanistan between 2005 and 2013, a period of expansion of public health services. New visits to outpatient clinics constituted the denominator for calculating proportions. In 2013, almost three-quarters of all new visits of children to public health services were for an infectious disease, with respiratory infections the most common. Because of inconsistent data collection for some infections early in the period, the trend for infectious diseases as a whole cannot be estimated. However, there was a statistically significant downward trend in the proportion of new visits that were diagnosed as one of the 11 leading communicable diseases from 74.5% in 2005 to 62.1% in 2013 (P < 0.001). There was no difference in communicable disease patterns between provinces, but a higher per capita consultation rate was associated with a higher proportion of the leading infections (P = 0.008). Recent improvements in maternal health, hygiene, and preventive services may have had an impact in reducing the burden of infections. ‫الصحية‬