Background: Recently there has been dramatic increase in the use of mobile technologies for health (m-Health) in both high and low- and middle-income countries (LMICs). However, little is known whether m-Health interventions in LMICs are based on relevant theories critical for effective implementation of such interventions. This review aimed to systematically identify m-Health studies on health behavioral changes in LMICs and to examine how each study applied behavior change theories. Materials and Methods: A systematic review was conducted using the standard method from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. By searching electronic databases (MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials [CENTRAL]), we identified eligible studies published in English from inception to June 30, 2017. For the identified m-Health studies in LMICs, we examined their theoretical bases, use of behavior change techniques (BCTs), and modes of delivery. Results: A total of 14 m-Health studies on behavioral changes were identified and, among them, only 5 studies adopted behavior change theory. The most frequently cited theory was the health belief model, which was adopted in three studies. Likewise, studies have applied only a limited number of BCTs. Among the seven BCTs identified, the most frequently used one was the social support (practical) technique for medication reminder and medical appointment. m-Health studies in LMICs most commonly used short messaging services and phone calls as modes of delivery for behavior change interventions. Conclusions: m-Health studies in LMICs are suboptimally based on behavior change theory yet. To maximize effectiveness of m-Health, rigorous delivery methods as well as theory-based intervention designs will be needed.

Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran’s I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended.

A maternal group B streptococcal (GBS) vaccine could prevent neonatal sepsis and meningitis. Its cost-effectiveness in low-income sub-Saharan Africa, a high burden region, is unknown. We used a decision tree model, with Markov nodes to project infants' lifetimes, to compare maternal immunization delivered through routine antenatal care with no immunization. 37 countries were clustered on the basis of economic and health resources and past public health performance. Vaccine efficacy for covered serotypes was ranged from 50% to 90%. The model projected EOGBS (early-onset) and LOGBS (late-onset) cases and deaths, disability-adjusted life years (DALYs), healthcare costs (2014 US$), and cost-effectiveness for a representative country in each of the four clusters: Guinea-Bissau, Uganda, Nigeria, and Ghana. Maximum vaccination costs/dose were estimated to meet two cost-effectiveness benchmarks, 0.5 GDP and GDP per capita/DALY, for ranges of disease incidence (reported and adjusted for under-reporting) and vaccine efficacy. At coverage equal to the proportion of pregnant women with≥4 antenatal visits (ANC4) and serotype-specific vaccine efficacy of 70%, maternal GBS immunization would prevent one-third of GBS cases and deaths in Uganda and Nigeria, where ANC4 is 50%, 42-43% in Guinea-Bissau (ANC4=65%), and 55-57% in Ghana (ANC4=87%). At a vaccination cost of $7/dose, maternal immunization would cost $320-$350/DALY averted in Guinea-Bissau, Nigeria, and Ghana, less than half these countries' GDP per capita. In Uganda, which has the lowest case fatality ratios, the cost would be $573/DALY. If the vaccine prevents a small proportion of stillbirths, it would be even more cost-effective. Vaccination cost/dose, disease incidence, and case fatality were key drivers of cost/DALY in sensitivity analyses. Maternal GBS immunization could be a cost-effective intervention in low-income sub-Saharan Africa, with cost-effectiveness ratios similar to other recently introduced vaccines. The vaccination cost at which introduction is cost-effective depends on disease incidence and vaccine efficacy. Clinical Trial registry name and registration number: Not applicable.

Background: The COVID-19 pandemic has disrupted malaria control activities globally. Notably, high levels of excess malaria morbidity and mortality in low- and middle-income countries (LMICs) were reported. Although it is crucial to systematically understand the main causes of the disruption to malaria control and synthesize strategies to prepare for future pandemics, such studies are scarce. Therefore, this study aims to better identify barriers against and strategies for malaria control. Methods: Following the PRISMA guidelines and through searches of electronic databases and Google Scholar, a systematic literature review was conducted to identify studies pertaining to malaria control published between January 2020 and December 2021. Only studies that discussed reported barriers and/or strategies related to malaria were included for the review. The Mixed Methods Quality Appraisal Tool (MMAT) and the Authority, Accuracy, Coverage, Objectivity, Date and Significance (AACODS) checklist were used for quality appraisal. Key information such as literature type, study design, setting and population, interventions, outcomes, barriers, and strategies were extracted. With an existing framework of four dimensions (accessibility, affordability, availability, and acceptability) further subdivided by the supply and demand sides, this study synthesized information on barriers and strategies related to malaria control and further categorized the strategies based on the time frame. Results: From the 30 selected studies, 27 barriers and 39 strategies were identified. The lockdown measures, which mainly threatened geographic accessibility and availability of malaria control services, were identified to be the main barrier hindering effective mobilization of community health workers and resources. Among the identified strategies, clear risk communication strategies would alleviate psychosocial barriers, which challenged acceptability. Some strategies that cross-cut points across all four dimensions would, require systems-level integration to enhance availability and affordability of malaria control. The strategies were distinguished between short-term, for instant response, and mid to long-term for future readiness. Conclusions: The pandemic resulted in complex barriers to malaria control, particularly imposing a double burden on LMICs. Identifying strategies to overcome said barriers provides useful insights in the decision-making processes for the current and future pandemic. Cross-cutting strategies that integrate all dimensions need to be considered. Health system strengthening and resilience strategy appropriate for country-specific context is fundamental.