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The global elimination of lymphatic filariasis (LF) is a major focus of the World Health Organization. One key challenge is locating residual infections that can perpetuate the transmission cycle. We show how a targeted sampling strategy using predictions from a geospatial model, combining random forests and geostatistics, can improve the sampling efficiency for identifying locations with high infection prevalence. Predictions were made based on the household locations of infected persons identified from previous surveys, and environmental variables relevant to mosquito density. Results show that targeting sampling using model predictions would have allowed 52% of infections to be identified by sampling just 17.7% of households. The odds ratio for identifying an infected individual in a household at a predicted high risk compared to a predicted low risk location was 10.2 (95% CI 4.2-22.8). This study provides evidence that a 'one size fits all' approach is unlikely to yield optimal results when making programmatic decisions based on model predictions. Instead, model assumptions and definitions should be tailored to each situation based on the objective of the surveillance program. When predictions are used in the context of the program objectives, they can result in a dramatic improvement in the efficiency of locating infected individuals.

Background: To determine the prevalence of enteric infections in Aboriginal children aged 0-2 years using conventional and molecular diagnostic techniques and to explore associations between the presence of pathogens and child growth.Methods: Cross-sectional analysis of Aboriginal children (n = 62) residing in a remote community in Northern Australia, conducted from July 24th - October 30th 2017. Stool samples were analysed for organisms by microscopy (directly in the field and following fixation and storage in sodium-acetate formalin), and by qualitative PCR for viruses, bacteria and parasites and serology for Strongyloides-specific IgG. Child growth (height and weight) was measured and z scores calculated according to WHO growth standards.Results: Nearly 60% of children had evidence for at least one enteric pathogen in their stool (37/62). The highest burden of infection was with adenovirus/sapovirus (22.9%), followed by astrovirus (9.8%) and Cryptosporidium hominis/parvum (8.2%). Non-pathogenic organisms were detected in 22.5% of children. Ten percent of children had diarrhea at the time of stool collection. Infection with two or more pathogens was negatively associated with height for age z scores (- 1.34, 95% CI - 2.61 to - 0.07), as was carriage of the non-pathogen Blastocystis hominis (- 2.05, 95% CI - 3.55 to - 0.54).Conclusions: Infants and toddlers living in this remote Northern Australian Aboriginal community had a high burden of enteric pathogens and non-pathogens. The association between carriage of pathogens/non-pathogens with impaired child growth in the critical first 1000 days of life has implications for healthy child growth and development and warrants further investigation. These findings have relevance for many other First Nations Communities that face many of the same challenges with regard to poverty, infections, and malnutrition. [ABSTRACT FROM AUTHOR]

The Menzies Remote Short-item Dietary Assessment Tool (MRSDAT) can be used to derive a dietary index score, which measures the degree of compliance with the Australian Dietary Guidelines. This study aimed to determine the relative validity of a dietary index score for children aged 6⁻24 months, living in a Remote Aboriginal Community (RAC), derived using MRSDAT. This validation study compared dietary index scores derived using MRSDAT with those derived from the average of three 24-h recalls. Participants were aged 6⁻36 months at the first dietary assessment and were living in a RAC. The level of agreement between the two methods was explored using Lin’s concordance correlation coefficient (CCC), Bland-Altman plots, weighted Cohen’s kappa, and Fischer’s exact and paired t -tests. Forty participants were recruited. The CCC was poor between methods ( R = 0.35, 95% CI 0.06, 0.58), with MRSDAT estimating higher dietary intake scores for all food groups except fruit, and higher dietary quality scores by an average of 4.78 points/100. Community-based Aboriginal researchers were central to this validation study. MRSDAT was within the performance range of other short-item dietary assessment tools developed for young children, and shows promise for use with very young children in RACs.