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"Participatory Mapping to Identify and Support At-Risk Populations in Emergency Preparedness" – Phase 3

Generic Clearance for CDC/ATSDR Formative Research and Tool Development

OMB Control No. 0920-1154

December 18, 2019

Supporting Statement B

CDC Contact:

Tracy N. Thomas, MSc, MPH

Senior Health Scientist

Center for Preparedness and Response (CPR)

Centers for Disease Control and Prevention

1600 Clifton Rd NE MS D75

Atlanta, GA 30333

Tel: 770-488-1570

BB: 404-772-1447

Email: tct5@cdc.gov

Table of Contents

Collection of Information employing Statistical Methods

1. Respondent Universe and Sampling Methods

2. Procedures for the Collection of Information

3. Methods to Maximize Response Rates and Deal with Non response

4. Tests of Procedures or Methods to be Undertaken

5. Individuals Consulted on Statistical Aspects and Individuals Collecting and/or Analyzing Data

B. Collections of Information Employing Statistical Methods

1. Respondent Universe and Sampling Methods

Non-probability convenience sampling will be used to identify disaster planners from multiple organizations to conduct a discussion-based exercise. From these initial contacts, snowballing will be used to identify additional participants. It is participants in the table top exercise to whom we will administer the survey. We estimate there will be 20 participants in the table top exercise in each of the two communities (i.e. Puerto Rico and Massachusetts), thereby yielding a total of 40 surveys recruited from a base of 70.

2. Procedures for the Collection of Information

In this project, the staff from Harvard T.H. Chan School of Public Health will administer a web-based survey for disaster planners through two collaborating community-based organizations (CBOs): Institute for Health Communication in San Juan (Puerto Rico) and the Massachusetts Association of Health Boards (Massachusetts). The Harvard research team has pre-existing partnerships with these organizations, both of which serve at-risk populations through a wide range of public health emergencies due to their geographic locations (i.e. Zika in Puerto Rico, snow storms in Massachusetts).

This is the third part of a three-part data collection effort. This GenIC submission is to conduct a web-based survey following a discussion-based exercise hosted by MAHB and IHC for disaster planners. In January 2020 we will administer the web-based survey. Specifically, the survey is designed to gather feedback on two elements introduced in the exercises: the concept of local knowledge and the data on local knowledge provided by the app with the goal of understanding: 1) the usefulness of local knowledge for planning for disasters, particularly for at-risk populations and 2) the utility of the data provided by the mobile app to collect local knowledge for disaster planning.

3. Methods to Maximize Response Rates and Deal with No Response

The Harvard T.H. Chan School of Public Health research group has sub-contracts with the participating CBOs (MAHB and IHC), who will assist the Harvard team in recruiting disaster planners to target for participating in a survey. Convenience sampling of referrals made by disaster planners and developing survey questions focused on community efforts that excludes the collection of personal identifiable and sensitive information will significantly minimize non-responses among participants.

4. Test of Procedures or Methods to Be Undertaken

Questions included in this data collection instrument were informed using results from two data collection instruments approved in ICR requests 201610-0920-009

5. Individuals Consulted on Statistical Aspects and Individuals Collecting and/or Analyzing Data

The data collected will be qualitative in nature and analyzed by the team members at the Harvard T.H. Chan School of Public Health. However, staff from OSPHP will provide substantial technical assistance and oversight in the analysis and interpretation of the results.

The thematic analysis will be conducted independently by at least two researchers and cross-checked for consistency. Disagreements will be resolved through consultations. The Nvivo 12 software will be used.

The findings from this analysis will be shared with the participating CBOs and disaster planners, but will not be generalized beyond the scope of each study site or to broader populations.

Finally, it is anticipated the findings will support efforts of the Office of Science and Public Health Practice (OSPHP) in the Center for Preparedness and Response (CPR) to increase capacity to identify at-risk populations and to advocate for their unique needs. Additionally, this work will add to OSPHP's broad project portfolio to mitigate adverse impacts on at-risk populations and identify optimal communication channels for reaching at-risk populations during emergencies. Moreover, findings from this project will provide CDC with the opportunity to leverage the science and innovations resulting from this effort to contribute to CDC’s improved efficiencies and effectiveness in emergency preparedness and response.

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