Setting priorities for humanitarian water, sanitation and hygiene research: a meeting report

Recent systematic reviews have highlighted a paucity of rigorous evidence to guide water, sanitation and hygiene (WASH) interventions in humanitarian crises. In June 2017, the Research for Health in Humanitarian Crises (R2HC) programme of Elhra, convened a meeting of representatives from international response agencies, research institutions and donor organisations active in the field of humanitarian WASH to identify research priorities, discuss challenges conducting research and to establish next steps. Topics including cholera transmission, menstrual hygiene management, and acute undernutrition were identified as research priorities. Several international response agencies have existing research programmes; however, a more cohesive and coordinated effort in the WASH sector would likely advance this field of research. This report shares the conclusions of that meeting and proposes a research agenda with the aim of strengthening humanitarian WASH policy and practice

Odds ratio’s for a shorter length of stay, as assessed by ordinal logistic regression (odds of an individual with a shorter length of stay falling in a category with less adequacy of water supply).

<p>Odds ratio’s for a shorter length of stay, as assessed by ordinal logistic regression (odds of an individual with a shorter length of stay falling in a category with less adequacy of water supply).</p

Comparison of the length of stay in an MSF feeding program versus adequacy of the village water supply.

<p>Comparison of the length of stay in an MSF feeding program versus adequacy of the village water supply.</p

Proportion of secondary infections among children from the 20 selected study villages presenting for primary care.

<p>Proportion of secondary infections among children from the 20 selected study villages presenting for primary care.</p

Spatial targeted vector control in the highlands of Burundi and its impact on malaria transmission-1

<p><b>Copyright information:</b></p><p>Taken from "Spatial targeted vector control in the highlands of Burundi and its impact on malaria transmission"</p><p>http://www.malariajournal.com/content/6/1/158</p><p>Malaria Journal 2007;6():158-158.</p><p>Published online 3 Dec 2007</p><p>PMCID:PMC2217530.</p><p></p>usters in the hill top were selected from 100 to 600 metres from the limit separating valley and hill top

Weekly number of suspected cases of typhoid fever, by date of symptom onset, registered in Harare, 10 October 2011–17 March 2012.

<p>Weekly number of suspected cases of typhoid fever, by date of symptom onset, registered in Harare, 10 October 2011–17 March 2012.</p

Numbers of suspected cases of typhoid fever, estimated population size, and attack rates by suburb, gender, and age group, in Dzivaresekwa and Kuwadzana suburbs, Harare, Zimbabwe, 10 October 2011–17 March 2012.

<p>Numbers of suspected cases of typhoid fever, estimated population size, and attack rates by suburb, gender, and age group, in Dzivaresekwa and Kuwadzana suburbs, Harare, Zimbabwe, 10 October 2011–17 March 2012.</p

Intensities of a) control points (representing the distribution of residential areas) and of b) suspected cases of typhoid fever, measured as events per km², in Dzivaresekwa and Kuwadzana suburbs, Harare, Zimbabwe, 10 October 2011–17 March 2012.

<p>Intensities of a) control points (representing the distribution of residential areas) and of b) suspected cases of typhoid fever, measured as events per km², in Dzivaresekwa and Kuwadzana suburbs, Harare, Zimbabwe, 10 October 2011–17 March 2012.</p

Geographical distribution of the log relative risk of typhoid fever in Dzivaresekwa and Kuwadzana suburbs in Harare, Zimbabwe, October 10 2011–March 17 2012, according to different bandwidths used for calculating the kernel function.

<p>Geographical distribution of the log relative risk of typhoid fever in Dzivaresekwa and Kuwadzana suburbs in Harare, Zimbabwe, October 10 2011–March 17 2012, according to different bandwidths used for calculating the kernel function.</p

Differences of K functions (red line) and 95% confidence envelope (blue lines) between suspected cases of typhoid fever and controls in Dzivaresekwa and Kuwadzana suburbs in Harare, Zimbabwe, 10 October 2011–17 March 2012.

<p>Differences of K functions (red line) and 95% confidence envelope (blue lines) between suspected cases of typhoid fever and controls in Dzivaresekwa and Kuwadzana suburbs in Harare, Zimbabwe, 10 October 2011–17 March 2012.</p