Indian healthcare system is in immediate need of a new healthcare delivery model to increase healthcare accessibility and improve the health outcomes of the marginalized. Inaccessibility and underutilization of Primary Health Centers (PHCs) disproportionately affect people living in remote areas. It is thus imperative for the designers, engineers, health professionals, and policymakers to come together with a collaborative mindset to develop innovative interventions that sustainably manage the accessibility of PHCs at large, promote preventive health, and thus improve the health outcomes of hard-to-reach communities. This article examines the available literature on barriers to primary healthcare in Indian context, the reason of failure of PHCs and the way forward. The article further analysis literature on existing Mobile Medical Units (MMUs) as an alternate solution to conventional PHCs and attempt to extract the major lessons to propose a mobile Primary Health Center (mPHC) in contrast to the existing conventional static PHCs. The intention is to find out the research gaps in the existing literature and try to address the same for future researchers, designers, engineers, health professionals and policy makers to think forward to make this idea of a mobile Primary Health Center (mPHC), as the main delivery model to cater basic healthcare services to the underserved communities.

Vaccines prevent 4-5 million deaths every year, but inequities in vaccine coverage persist among key disadvantaged subpopulations. Under-immunized subpopulations (e.g., migrants, slum residents) may be consistently missed with conventional methods for estimating immunization coverage and assessing vaccination barriers. Adaptive sampling, such as respondent-driven sampling, may offer useful strategies for identifying and collecting data from these subpopulations that are often \"hidden\" or hard-to-reach. However, use of these adaptive sampling approaches in the field of global immunization has not been systematically documented. We searched PubMed, Scopus, and Embase databases to identify eligible studies published through November 2020 that used an adaptive sampling method to collect immunization-related data. From the eligible studies, we extracted relevant data on their objectives, setting and target population, and sampling methods. We categorized sampling methods and assessed their frequencies. Twenty-three studies met the inclusion criteria out of the 3069 articles screened for eligibility. Peer-driven sampling was the most frequently used adaptive sampling method (57%), followed by geospatial sampling (30%), venue-based sampling (17%), ethnographic mapping (9%), and compact segment sampling (9%). Sixty-one percent of studies were conducted in upper-middle-income or high-income countries. Data on immunization uptake were collected in 65% of studies, and data on knowledge and attitudes about immunizations were collected in 57% of studies. We found limited use of adaptive sampling methods in measuring immunization coverage and understanding determinants of vaccination uptake. The current under-utilization of adaptive sampling approaches leaves much room for improvement in how immunization programs calibrate their strategies to reach \"hidden\" subpopulations.

Human trafficking has long-lasting implications for the well-being of trafficked people, families, and affected communities. Prevention and intervention efforts, however, have been stymied by a lack of information on the scale and scope of the problem. Because trafficked people are mostly hidden from view, traditional methods of establishing prevalence can be prohibitively expensive in the recruitment, participation, and retention of survey participants. Also, trafficked people are not randomly distributed in the general population. Researchers have therefore begun to apply methods previously used in public health research and other fields on hard-to-reach populations to measure the prevalence of human trafficking. In this topical review, we examine how these prevalence methods used for hard-to-reach populations can be used to measure the prevalence of human trafficking. These methods include network-based approaches, such as respondent-driven sampling and the network scale-up method, and venue-based methods. Respondent-driven sampling is useful, for example, when little information about the trafficked population has been produced and when an adequate sampling frame does not exist. The network scale-up method is unique in that it does not target the hidden population directly. The implications of our work internationally include the need for documenting and validating the various prevalence estimation methods in the United States in a more robust way than was done in existing efforts. In providing this roadmap for estimating the prevalence of human trafficking, our overarching goal is to promote the equitable treatment and overall well-being of the socially disadvantaged populations who disproportionately experience human trafficking.

Web-based respondent-driven sampling is a novel sampling method for the recruitment of participants for generating population estimates, studying social network characteristics, and delivering health interventions. However, the application, barriers and facilitators, and recruitment performance of web-based respondent-driven sampling have not yet been systematically investigated.
Our objectives were to provide an overview of published research using web-based respondent-driven sampling and to investigate factors related to the recruitment performance of web-based respondent-driven sampling.
We conducted a scoping review on web-based respondent-driven sampling studies published between 2000 and 2019. We used the process evaluation of complex interventions framework to gain insights into how web-based respondent-driven sampling was implemented, what mechanisms of impact drove recruitment, what the role of context was in the study, and how these components together influenced the recruitment performance of web-based respondent-driven sampling.
We included 18 studies from 8 countries (high- and low-middle income countries), in which web-based respondent-driven sampling was used for making population estimates (n=12), studying social network characteristics (n=3), and delivering health-related interventions (n=3). Studies used web-based respondent-driven sampling to recruit between 19 and 3448 participants from a variety of target populations. Studies differed greatly in the number of seeds recruited, the proportion of successfully recruiting participants, the number of recruitment waves, the type of incentives offered to participants, and the duration of data collection. Studies that recruited relatively more seeds, through online platforms, and with less rigorous selection procedures reported relatively low percentages of successfully recruiting seeds. Studies that did not offer at least one guaranteed material incentive reported relatively fewer waves and lower percentages of successfully recruiting participants. The time of data collection was shortest in studies with university students.
Web-based respondent-driven sampling can be successfully applied to recruit individuals for making population estimates, studying social network characteristics, and delivering health interventions. In general, seed and peer recruitment may be enhanced by rigorously selecting and motivating seeds, offering at least one guaranteed material incentive, and facilitating adequate recruitment options regarding the target population\'s online connectedness and communication behavior. Potential trade-offs should be taken into account when implementing web-based respondent-driven sampling, such as having less opportunities to implement rigorous seed selection procedures when recruiting many seeds, as well as issues around online rather than physical participation, such as the risk of cheaters participating repeatedly.

We completed a scoping review to: (1) identify strategies that have been used to engage hard-to-reach populations in childhood disability research, and (2) synthesize information as to whether and how these strategies were evaluated.
Systematic search of six electronic databases and grey literature to identify articles published in the last 10 years. Studies published in English, French, and Spanish reporting on strategies used to engage hard-to-reach populations in childhood disability research were eligible for inclusion.
Out of 106 articles selected for full text review, 16 were included. Engagement was more common in earlier stages of research. The populations included in studies were children with disabilities and their parents. Engagement strategies were reported but rarely evaluated. Anecdotal outcomes of engagement were reported in 14/16 studies and included positive outcomes for the children and parents such as empowerment. The challenges with engagement included the increased time needed to engage children with disabilities or their parents.
Our results can guide others who wish to engage a diverse group of children with disabilities and their parents in research. Research on how to engage other hard-to-reach populations within the childhood disability umbrella and evaluation of engagement strategies and outcomes is needed.IMPLICATIONS FOR REHABILITATION• Service providers should be concerned when the research informing their practices does not include families that represent their clients (e.g., families who are low income, Indigenous, ethnic minority, or LGBTQI parents of children with disabilities).• Strategies used to include children with disabilities in research, such as offering varied response methods that include story telling or photography, may also be used to promote participation in clinical services.• Service providers and teachers may have a role in facilitating the recruitment of \'hard-to-reach\' families in research and advising researchers on methods to create a comfortable environment with accessible means of data collection for children with disabilities.

BACKGROUND: \'Hard-to-reach\' is a term used to describe those sub-groups of the population that may be difficult to reach or involve in research or public health programmes. Application of a single term to call these sub-sections of populations implies a homogeneity within distinct groups, which does not necessarily exist. Different sampling techniques were introduced so far to recruit hard-to-reach populations. In this article, we have reviewed a range of ap-proaches that have been used to widen participation in studies.
METHODS: We performed a Pubmed and Google search for relevant English language articles using the keywords and phrases: (hard-to-reach AND population* OR sampl*), (hidden AND population* OR sample*) and (\"hard to reach\" AND population* OR sample*) and a consul-tation of the retrieved articles\' bibliographies to extract empirical evidence from publications that discussed or examined the use of sampling techniques to recruit hidden or hard-to-reach populations in health studies.
RESULTS: Reviewing the literature has identified a range of techniques to recruit hard-to-reach populations, including snowball sampling, respondent-driven sampling (RDS), indigenous field worker sampling (IFWS), facility-based sampling (FBS), targeted sampling (TS), time-location (space) sampling (TLS), conventional cluster sampling (CCS) and capture re-capture sampling (CR).
CONCLUSIONS: The degree of compliance with a study by a certain \'hard-to-reach\' group de-pends on the characteristics of that group, recruitment technique used and the subject of inter-est. Irrespective of potential advantages or limitations of the recruitment techniques reviewed, their successful use depends mainly upon our knowledge about specific characteristics of the target populations. Thus in line with attempts to expand the current boundaries of our know-ledge about recruitment techniques in health studies and their applications in varying situa-tions, we should also focus on possibly all contributing factors which may have an impact on participation rate within a defined population group.