The winding road to health: A systematic scoping review on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries

Abstract

Background Geographical accessibility to healthcare is an important component of infectious disease dynamics. Timely access to health facilities can prevent disease progression and enables disease notification through surveillance systems. The importance of accounting for physical accessibility in response to infectious diseases is increasingly recognized. Yet, there is no comprehensive review of the literature available on infectious diseases in relation to geographical accessibility to care. Therefore, we aimed at evaluating the current state of knowledge on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries. Methods and findings A search strategy was developed and conducted on Web of Science and PubMed on 4 March 2019. New publications were checked until May 28, 2020. All publication dates were eligible. Data was charted into a tabular format and descriptive data analyses were carried out to identify geographical regions, infectious diseases, and measures of physical accessibility among other factors. Search queries in PubMed and Web of Science yielded 560 unique publications. After title and abstract screening 99 articles were read in full detail, from which 64 articles were selected, including 10 manually. Results of the included publications could be broadly categorized into three groups: (1) decreased spatial accessibility to health care was associated with a higher infectious disease burden, (2) decreased accessibility was associated to lower disease reporting, minimizing true understanding of disease distribution, and (3) the occurrence of an infectious disease outbreak negatively impacted health care accessibility in affected regions. In the majority of studies, poor geographical accessibility to health care was associated with higher disease incidence, more severe health outcomes, higher mortality, and lower disease reporting. No difference was seen between countries or infectious diseases. Conclusions Currently, policy-makers and scientists rely on data collected through passive surveillance systems, introducing uncertainty on disease estimates for remote communities. Our results highlight the need for increasing integration of geographical accessibility measures in disease risk modelling, allowing more realistic disease estimates and enhancing our understanding of true disease burden. Additionally, disease risk estimates could be used in turn to optimize the allocation of health services in the prevention and detection of infectious diseases.

Every Child on the Map: A Theory of Change Framework for Improving Childhood Immunization Coverage and Equity Using Geospatial Data and Technologies

“…Even with good population estimates, the location of settlements in relation to services measured by distance or travel time impact access and coverage. There is a relationship between complete and timely vaccination status and shorter distance or travel time to the nearest vaccination service, demonstrating how important the location of immunization services and geographic accessibility is for maximal immunization coverage [1,[22][23][24][25]. To calculate unmet need, aggregate vaccination coverage data for the entire country or province can hide pockets of low coverage and settlements with unvaccinated children, leaving these communities vulnerable to vaccine-preventable diseases [26,27].…”

Clinical Cholera Surveillance Sensitivity in Bangladesh and Implications for Large-Scale Disease Control

“…We assumed that hospital catchment areas could be defined with simple radial buffers, similar to previous work [ 15 ]. A more accurate approach to estimating hospital catchment areas would use patient demographic, symptom, and home address data and account for barriers to healthcare seeking [ 16 , 17 ]; in reality, the cholera surveillance zone is likely smaller than what we assumed resulting in overestimates of system sensitivity. In contrast, the functional coverage of the cholera surveillance zone may be more expansive than our stated assumptions if private clinics and facilities outside of the national sentinel surveillance system use RDTs or culture to confirm suspected cholera cases, and event-based surveillance systems like media surveillance and hotlines routinely detect disease outbreaks, although samples still have to be processed and confirmed in a laboratory [ 18 ].…”

Clinical cholera surveillance sensitivity in Bangladesh and implications for large-scale disease control

“…We assumed that hospital catchment areas could be defined with simple radial buffers, similar to previous work [14]. A more accurate approach to estimating hospital catchment areas would use patient demographic, symptom, and home address data, and account for barriers to healthcare seeking [15,16]; in reality, the cholera surveillance zone is likely smaller than what we assumed resulting in overestimates of system sensitivity. Conversely, the functional coverage of the cholera surveillance zone may be more expansive than our stated assumptions if private clinics and facilities outside of the national sentinel surveillance system use RDTs or culture to confirm suspected cholera cases, and event-based surveillance systems like media surveillance and hotlines routinely detect disease outbreaks, though samples still have to be processed and confirmed in a lab [17].…”