[Accepted Manuscript] Anthropometry and Malaria among Children in Niger: A Cross-Sectional Study.

The complex relationship between malnutrition and malaria affects morbidity and mortality in children younger than 5 years, particularly in parts of sub-Saharan Africa where these conditions occur together seasonally. Previous research on this relationship has been inconclusive. Here, we examine the association between anthropometric indicators and malaria infection in a population-based sample of children younger than 5 years in Niger. This cross-sectional study is a secondary analysis of a cluster-randomized trial comparing treatment strategies for trachoma in Niger. We included children aged 6-60 months residing in the 48 communities enrolled in the trial who completed anthropometric and malaria infection assessments at the final study visit. We evaluated the association between anthropometric indicators, including height-for-age z-score (HAZ) and weight-for-age z-score (WAZ) and indicators of malaria infection, including malaria parasitemia and clinical malaria. In May 2013, we collected data from 1,649 children. Of these, 780 (47.3%) were positive for malaria parasitemia and 401 (24.3%) had clinical malaria. In models of malaria parasitemia, the adjusted odds ratio (aOR) was 1.05 (95% confidence interval [CI]: 1.00-1.10) for HAZ and 1.07 (95% CI: 0.99, 1.15) for WAZ. In models of clinical malaria, the aOR was 1.07 (95% CI: 1.02-1.11) for HAZ and 1.09 (95% CI: 1.01-1.19) for WAZ. Overall, we did not find evidence of an association between most anthropometric indicators and malaria infection. Greater height may be associated with an increased risk of clinical malaria

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020

Strengthening data collection for neglected tropical diseases:What data are needed for models to better inform tailored intervention programmes?

Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases

Prophylactic antibiotic regimens in tumour surgery (PARITY) A PILOT MULTICENTRE RANDOMISED CONTROLLED TRIAL

Optimising joint reconstruction management in arthritis and bone tumour patient