Evaluation of consistent use, barriers to use, and microbiological effectiveness of three prototype household water treatment technologies in Haiti, Kenya, and Nicaragua.

Household water treatment (HWT) can improve drinking water quality and reduce diarrheal disease. New HWT technologies are typically evaluated under ideal conditions; however, health gains depend on consistent, effective household use, which is less often evaluated. We conducted four evaluations of three prototype HWT technologies: two filters and one electrochlorinator. Evaluations consisted of a baseline survey, HWT distribution to households (ranging from 60 to 82), and four visits (ranging from 1 week-14 months after distribution). Each visit included a survey, observation of treated water presence (confirmed use), and microbiological analysis of treated and untreated samples for E. coli. Consistent use was defined as the proportion of total visits with confirmed use. Overall, confirmed use declined 2.54% per month on average, and 2-72% of households demonstrated 100% consistent use. Consistent use was positively associated with baseline HWT knowledge and practice and belief that drinking water was unsafe, and negatively associated with technological problems. Reported barriers to use were behavioral, such as forgetting or when outside the home, and technological failures. Technologies demonstrated 68-96% E. coli reductions, with 18-70% of treated samples having detectable E. coli. Results highlight the importance of household use evaluations within prototype HWT technology design cycles, the need for standard evaluation metrics, and difficulties in achieving both consistent use and microbiological effectiveness with HWT technologies.

Post-treatment Lyme disease symptoms score: Developing a new tool for research.

Some patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with and without residual symptoms. There was a strong correlation between sleep disturbance and certain other symptoms such as fatigue, pain, anxiety, and cognitive complaints. Results were subjected to a Logistic Regression model using the Neuro-QoL Fatigue t-score together with Short Form-36 Physical Functioning scale and Mental Health component scores; and to a Decision Tree model using only the QoL Fatigue t-score. The Logistic Regression model had an accuracy of 97% and Decision Tree model had an accuracy of 93%, when compared with clinical categorization. The Logistic Regression and Decision Tree models were then applied to a separate cohort. Both models performed with high sensitivity (90%), but moderate specificity (62%). The overall accuracy was 74%. Agreement between 2 time points, separated by a mean of 4 months, was 89% using the Decision Tree model and 87% with the Logistic Regression model. These models are simple and can help to quantitate the level of symptom severity in post-treatment Lyme disease symptoms. More research is needed to increase the specificity of the models, exploring additional approaches that could potentially strengthen an operational definition for post-treatment Lyme disease symptoms. Evaluation of how sleep disturbance, fatigue, pain and cognitive complains interrelate can potentially lead to new interventions that will improve the overall health of these patients.