Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

A comparison of 3 rheumatoid arthritis disease activity indices in routine clinical practice

Objective: The objective of this study was to appraise the correlation and agreement of RAPID 3 with DAS 28 and CDAI in terms of measuring disease activity/severity and for monitoring response to treatment at 2 and 4 month follow up. Methods: 105 adult literate persons having rheumatoid arthritis according to the 2010 ACR EULAR revised criteria were included. They were evaluated for disease activity by DAS 28, CDAI, and RAPID 3 scores. Response to treatment at 2 month and 4 month follow up was measured by these scores. Achievement of treatment target was defined as conversion from high/moderate disease activity at initial visit to low activity/remission at follow up visit. Result: The mean DAS 28 (0-10), CDAI (0-76) , RAPID 3 (0-30) were 4.73 , 16.72, 10.72 respectively. There was substantial agreement between DAS 28 and RAPID 3 severity categories (kappa = 0.959, P < 0.0001) and also between CDAI and RAPID 3. Conclusion: In a busy clinical setting, our study has shown usefulness of RAPID3 compared to the two most commonly used indices to assess disease activity in RA, both in terms of measuring quantitative disease activity as well as monitoring of treatment response at follow up visits

Suitable methods for isolation, culture, storage and identification of wheat blast fungus Magnaporthe oryzae Triticum pathotype

Wheat blast disease caused by a South American lineage of Magnaporthe oryzae Triticum (MoT) pathotype has emerged as a serious threat to wheat production in Bangladesh since its first emergence in 2016. Efficient and suitable methods for isolation, storage, inoculum production and molecular characterization of the pathogen can help in achieving the target of sustainable management of the disease in a relatively short period of time. In this study, we aimed to develop suitable methods for isolation, storage and morphological characterization and molecular identification of MoT isolates collected from the blast-infected wheat fields in Bangladesh. This process included modification of existing protocols that were available for a related fungal pathogen M. oryzae or de novo method development and validation. We developed suitable methods for isolation of MoT from field-infected plant samples using modified monoconidial isolation technique and produced abundant conidia from a single mycelial plate for in vivo pathogenicity assay in a reproducible manner. Cultural and morphological characterization of the isolates revealed that all Bangladeshi MoT isolates are of a single clonal lineage with similar cultural and morphological characters. Molecular detection of isolates with M. oryzae-specific primers Pot1 and Pot2 and MoTspecific primers MoT3F and MoT3R produced bands with the expected size from all wheat-infecting isolates. We also successfully established a PCR-based detection system based on a commercially available detection kit for fieldinfected leaf and seed samples by detecting Pot2- and MoT3-specific bands. Additionally, the simple method we developed in our study for producing abundant conidia in a very short period of time will be very helpful in studying biology of the wheat blast fungus. This method was also proven to be more user-friendly and costeffective than previously available methods. Successful characterization of MoT isolates at morphological and molecular levels coupled with detection of the pathogen in infected field and seed lots should be useful for efficient surveillance and management of the fearsome wheat blast disease

Emergence of wheat blast in Bangladesh was caused by a South American lineage of Magnaporthe oryzae

In February 2016, a new fungal disease was spotted in wheat fields across eight districts in Bangladesh. The epidemic spread to an estimated 15,741 hectares, about 16% of cultivated wheat area in Bangladesh, with yield losses reaching up to 100%. Within weeks of the onset of the epidemic, we performed transcriptome sequencing of symptomatic leaf samples collected directly from Bangladeshi fields. Population genomics analyses revealed that the outbreak was caused by a wheat-infecting South American lineage of the blast fungus Magnaporthe oryzae. We show that genomic surveillance can be rapidly applied to monitor plant disease outbreaks and provide valuable information regarding the identity and origin of the infectious agent