Effectiveness of a Mobile Short-Message-Service-Based Disease Outbreak Alert System in Kenya

A systematic review on mobile health applications for foodborne disease outbreak management

Background

Foodborne disease outbreaks are common and notifiable in South Africa; however, they are rarely reported and poorly investigated. Surveillance data from the notification system is suboptimal and limited, and does not provide adequate information to guide public health action and inform policy. We performed a systematic review of published literature to identify mobile application-based outbreak response systems for managing foodborne disease outbreaks and to determine the elements that the system requires to generate foodborne disease data needed for public action.

Methods

Studies were identified through literature searches using online databases on PubMed/Medline, CINAHL, Academic Search Complete, Greenfile, Library, Information Science & Technology. Search was limited to studies published in English during the period January 1990 to November 2020. Search strategy included various terms in varying combinations with Boolean phrases “OR” and “AND”. Data were collected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. A standardised data collection tool was used to extract and summarise information from identified studies. We assessed qualities of mobile applications by looking at the operating system, system type, basic features and functionalities they offer for foodborne disease outbreak management.

Results

Five hundred and twenty-eight (528) publications were identified, of which 48 were duplicates. Of the remaining 480 studies, 2.9% (14/480) were assessed for eligibility. Only one of the 14 studies met the inclusion criteria and reported on one mobile health application named MyMAFI (My Mobile Apps for Field Investigation). There was lack of detailed information on the application characteristics. However, based on minimal information available, MyMAFI demonstrated the ability to generate line lists, reports and offered functionalities for outbreak verification and epidemiological investigation. Availability of other key components such as environmental and laboratory investigations were unknown.

Conclusions

There is limited use of mobile applications on management of foodborne disease outbreaks. Efforts should be made to set up systems and develop applications that can improve data collection and quality of foodborne disease outbreak investigations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12283-6.

A scope of mobile health solutions in COVID-19 pandemics

Background and aim

COVID-19 has become an international emergency. The use of digital solutions can be effective in managing, preventing, and overcoming the further spread of infectious disease outbreaks. Accordingly, the use of mobile-health (m-health) technologies has the potential to promote public health. This review aimed to study the application of m-health solutions for the management of the COVID-19 outbreak.

Methods

The search strategy was done in Medline (PubMed), Embase, IEEE, and Google Scholar by using related keywords to m-health and COVID-19 on July 6, 2020. English papers that used m-health technologies for the COVID-19 outbreak were included.

Results

Of the 2046 papers identified, 16 were included in this study. M-health had been used for various aims such as early detection, fast screening, patient monitoring, information sharing, education, and treatment in response to the COVID-19 outbreak. M-health solutions were classified into four use case categories: prevention, diagnosis, treatment, and protection. The mobile phone-based app and short text massaging were the most frequently used modalities, followed by wearables, portable screening devices, mobile-telehealth, and continuous telemetry monitor during the pandemics.

Conclusion

It appears that m-health technologies played a positive role during the COVID-19 outbreak. Given the extensive capabilities of m-health solutions, investigation and use of all potential applications of m-health should be considered for combating the current Epidemics and mitigating its negative impacts.

Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review

The advances in mobile technologies and applications are driving the transformation in health services delivery globally. Mobile phone penetration is increasing exponentially in low-and middle-income countries, hence using mobile phones for healthcare services could reach more people in resource-limited settings than the traditional forms of healthcare provision. The review presents recent literature on facilitators and barriers of implementing mHealth for disease screening and treatment support in low-and middle-income countries. We searched for relevant literature from the following electronic databases: MEDLINE; CINAHL with full text via EBSCOhost; Science Direct; PubMed; Google Scholar and Web of Science using the keywords for relevant studies. We searched for published studies from 2015 to August 2020 with no language limitations. A total of 721 articles identified, 125 articles met the inclusion criteria and were included in the qualitative synthesis. The review demonstrates relevant facilitators for the implementation of mHealth, which includes knowledge, attitudes, and perceptions of stakeholders on the use of mHealth and the performance of mHealth for disease diagnosis in low and-middle-income countries. Barriers and challenges hindering the implementation of mHealth applications were also identified. We proposed a framework for improving the implementation of mHealth for disease screening and treatment support in low-and middle-income countries.

The use of mobile phones for the prevention and control of arboviral diseases: a scoping review

BACKGROUND

The rapid expansion of dengue, Zika and chikungunya with large scale outbreaks are an increasing public health concern in many countries. Additionally, the recent coronavirus pandemic urged the need to get connected for fast information transfer and exchange. As response, health programmes have -among other interventions- incorporated digital tools such as mobile phones for supporting the control and prevention of infectious diseases. However, little is known about the benefits of mobile phone technology in terms of input, process and outcome dimensions. The purpose of this scoping review is to analyse the evidence of the use of mobile phones as an intervention tool regarding the performance, acceptance, usability, feasibility, cost and effectiveness in dengue, Zika and chikungunya control programmes.

METHODS

We conducted a scoping review of studies and reports by systematically searching: i) electronic databases (PubMed, PLOS ONE, PLOS Neglected Tropical Disease, LILACS, WHOLIS, ScienceDirect and Google scholar), ii) grey literature, using Google web and iii) documents in the list of references of the selected papers. Selected studies were categorized using a pre-determined data extraction form. Finally, a narrative summary of the evidence related to general characteristics of available mobile health tools and outcomes was produced.

RESULTS

The systematic literature search identified 1289 records, 32 of which met the inclusion criteria and 4 records from the reference lists. A total of 36 studies were included coming from twenty different countries. Five mobile phone services were identified in this review: mobile applications (n = 18), short message services (n=7), camera phone (n = 6), mobile phone tracking data (n = 4), and simple mobile communication (n = 1). Mobile phones were used for surveillance, prevention, diagnosis, and communication demonstrating good performance, acceptance and usability by users, as well as feasibility of mobile phone under real life conditions and effectiveness in terms of contributing to a reduction of vectors/ disease and improving users-oriented behaviour changes. It can be concluded that there are benefits for using mobile phones in the fight against arboviral diseases as well as other epidemic diseases. Further studies particularly on acceptance, cost and effectiveness at scale are recommended.

Routine Health Information System (RHIS) improvements for strengthened health system management

BACKGROUND

A well-functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management.

OBJECTIVES

To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a 'similar articles' search in PubMed.

SELECTION CRITERIA

Randomised and non-randomised trials, controlled before-after studies and time-series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems.

DATA COLLECTION AND ANALYSIS

Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence.

MAIN RESULTS

We included six studies: four cluster randomised trials and two controlled before-after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web-based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper-based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious (misidentification) errors for TB test results compared to a paper-based system (very low certainty evidence). Misidentification errors are inaccuracies in transferring test results between an electronic register and patients' clinical charts. We are also uncertain about the effect of the intervention on service quality (timeliness of starting or changing a patient's TB treatment) (very low certainty evidence). A hand-held electronic device probably improves the length of time to report TB test results, and probably reduces the total frequency of recording errors in TB test results between the laboratory notebook and the electronic information record system, compared to a paper-based system (moderate-certainty evidence). We are, however, uncertain about the effect of the intervention on the frequency of serious (misidentification) errors in recording between the laboratory notebook and the electronic information record, compared to a paper-based system (very low certainty evidence). We are uncertain about the effect of a hospital electronic health information system on service quality (length of time outpatients spend at hospital, length of hospital stay, and hospital revenue collection), compared to a paper-based system (very low certainty evidence). High-intensity brief text messaging (SMS) may make little or no difference to data quality (in terms of completeness of documentation of pregnancy outcomes), compared to low-intensity brief text messaging (low-certainty evidence). We are uncertain about the effect of electronic drug stock notification (with either data management support or product transfer support) on service quality (in terms of transporting stock and stock levels), compared to paper-based stock notification (very low certainty evidence). We are uncertain about the effect of health information strengthening (where it is part of comprehensive service quality improvement intervention) on service quality (health worker motivation, receipt of training by health workers, health information index scores, quality of clinical observation of children and adults) (very low certainty evidence).

AUTHORS' CONCLUSIONS

The review indicates mixed effects of mainly technical interventions to improve data quality, with gaps in evidence on interventions aimed at enhancing data-informed health system management. There is a gap in interventions studying information support beyond clinical management, such as for human resources, finances, drug supply and governance. We need to have a better understanding of the causal mechanisms by which information support may affect change in management decision-making, to inform robust intervention design and evaluation methods.

Use of technology for public health surveillance reporting: opportunities, challenges and lessons learnt from Kenya

BACKGROUND

Effective public health surveillance systems are crucial for early detection and response to outbreaks. In 2016, Kenya transitioned its surveillance system from a standalone web-based surveillance system to the more sustainable and integrated District Health Information System 2 (DHIS2). As part of Global Health Security Agenda (GHSA) initiatives in Kenya, training on use of the new system was conducted among surveillance officers. We evaluated the surveillance indicators during the transition period in order to assess the impact of this training on surveillance metrics and identify challenges affecting reporting rates.

METHODS

From February to May 2017, we analysed surveillance data for 13 intervention and 13 comparison counties. An intervention county was defined as one that had received refresher training on DHIS2 while a comparison county was one that had not received training. We evaluated the impact of the training by analysing completeness and timeliness of reporting 15 weeks before and 12 weeks after the training. A chi-square test of independence was used to compare the reporting rates between the two groups. A structured questionnaire was administered to the training participants to assess the challenges affecting surveillance reporting.

RESULTS

The average completeness of reporting for the intervention counties increased from 45 to 62%, i.e. by 17 percentage points (95% CI 16.14-17.86) compared to an increase from 49 to 52% for the comparison group, i.e. by 3 percentage points (95% CI 2.23-3.77). The timeliness of reporting increased from 30 to 51%, i.e. by 21 percentage points (95% CI 20.16-21.84) for the intervention group, compared to an increase from 31 to 38% for the comparison group, i.e.by 7 percentage points (95% CI 6.27-7.73). Major challenges for the low reporting rates included lack of budget support from government, lack of airtime for reporting, health workers strike, health facilities not sending surveillance data, use of wrong denominator to calculate reporting rates and surveillance officers having other competing tasks.

CONCLUSIONS

Training plays an important role in improving public health surveillance reporting. However, to improve surveillance reporting rates to the desired national targets, other challenges affecting reporting must be identified and addressed accordingly.

CovidSens: a vision on reliable social sensing for COVID-19

With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from online users. In this paper, we propose CovidSens, a vision of social sensing-based risk alert systems to spontaneously obtain and analyze social data to infer the state of the COVID-19 propagation. CovidSens can actively help to keep the general public informed about the COVID-19 spread and identify risk-prone areas by inferring future propagation patterns. The CovidSens concept is motivated by three observations: (1) people have been actively sharing their state of health and experience of the COVID-19 via online social media, (2) official warning channels and news agencies are relatively slower than people reporting their observations and experiences about COVID-19 on social media, and (3) online users are frequently equipped with substantially capable mobile devices that are able to perform non-trivial on-device computation for data processing and analytics. We envision an unprecedented opportunity to leverage the posts generated by the ordinary people to build a real-time sensing and analytic system for gathering and circulating vital information of the COVID-19 propagation. Specifically, the vision of CovidSens attempts to answer the questions: How to distill reliable information about the COVID-19 with the coexistence of prevailing rumors and misinformation in the social media? How to inform the general public about the latest state of the spread timely and effectively, and alert them to remain prepared? How to leverage the computational power on the edge devices (e.g., smartphones, IoT devices, UAVs) to construct fully integrated edge-based social sensing platforms for rapid detection of the COVID-19 spread? In this vision paper, we discuss the roles of CovidSens and identify the potential challenges in developing reliable social sensing-based risk alert systems. We envision that approaches originating from multiple disciplines (e.g., AI, estimation theory, machine learning, constrained optimization) can be effective in addressing the challenges. Finally, we outline a few research directions for future work in CovidSens.

A Review of Mobile Health Applications in Epidemic and Pandemic Outbreaks: Lessons Learned for COVID-19

Context: Using smart mobile devices, called mobile health (mHealth), facilitates providing health services, speeds up the process, and reduces the costs and complications of direct services. Also, mHealth has many capabilities and applications in epidemic and pandemic outbreaks. This study aimed to identify mHealth applications in epidemic/pandemic outbreaks and provide some suggestions for tackling COVID-19. Methods: To find the relevant studies, searches were done in PubMed and Scopus by related keywords during 2014 - 2020 (March 10). After selecting the studies based on the inclusion and exclusion criteria, data were collected by a data-gathering form. Results: Of the 727 retrieved studies, 17 studies were included. All studies emphasized the positive effect of mHealth for use in epidemic/pandemic outbreaks. The main applications of mHealth for epidemic/pandemic outbreaks included public health aspects, data management, educational programs, diagnosis, and treatment. Conclusions: mHealth is an appropriate method for encountering epidemic/pandemic outbreaks due to its extensive applications. In the pandemic outbreak of COVID-19, mHealth is one of the best choices to use in the patient-physician relationship as tele-visits, using in fever coach, providing real-time information for healthcare providers, population monitoring, and detecting the disease based on obtained data from different locations.

Clinical Epidemiology of 7126 Melioidosis Patients in Thailand and the Implications for a National Notifiable Diseases Surveillance System

Background

National notifiable diseases surveillance system (NNDSS) data in developing countries are usually incomplete, yet the total number of fatal cases reported is commonly used in national priority-setting. Melioidosis, an infectious disease caused by Burkholderia pseudomallei, is largely underrecognized by policy-makers due to the underreporting of fatal cases via the NNDSS.

Methods

Collaborating with the Epidemiology Division (ED), Ministry of Public Health (MoPH), we conducted a retrospective study to determine the incidence and mortality of melioidosis cases already identified by clinical microbiology laboratories nationwide. A case of melioidosis was defined as a patient with any clinical specimen culture positive for B. pseudomallei. Routinely available microbiology and hospital databases of secondary care and tertiary care hospitals, the national death registry, and NNDSS data were obtained for analysis.

Results

A total of 7126 culture-confirmed melioidosis patients were identified from 2012 to 2015 in 60 hospitals countrywide. The total number of cases diagnosed in Northeast, Central, South, East, North, and West Thailand were 5475, 536, 374, 364, 358, and 19 cases, respectively. The overall 30-day mortality was 39% (2805/7126). Only 126 (4%) deaths were reported to the NNDSS. Age, presentation with bacteremia and pneumonia, prevalence of diabetes, and 30-day mortality differed by geographical region (all P < .001). The ED at MoPH has agreed to include the findings of our study in the next annual report of the NNDSS.

Conclusions

Melioidosis is an important cause of death in Thailand nationwide, and its clinical epidemiology may be different by region. In developing countries, NNDSS data can be supplemented by integrating information from readily available routine data sets.

Barriers to the Use of Mobile Health in Improving Health Outcomes in Developing Countries: Systematic Review

Background

The use of mobile health (mHealth) technologies to improve population-level health outcomes around the world has surged in the last decade. Research supports the use of mHealth apps to improve health outcomes such as maternal and infant mortality, treatment adherence, immunization rates, and prevention of communicable diseases. However, developing countries face significant barriers to successfully implement, sustain, and expand mHealth initiatives to improve the health of vulnerable populations.

Objective

We aimed to identify and synthesize barriers to the use of mHealth technologies such as text messaging (short message service [SMS]), calls, and apps to change and, where possible, improve the health behaviors and health outcomes of populations in developing countries.

Methods

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Deriving search criteria from the review’s primary objective, we searched PubMed and CINAHL using an exhaustive terms search (eg, mHealth, text messaging, and developing countries, with their respective Medical Subject Headings) limited by publication date, English language, and full text. At least two authors thoroughly reviewed each article’s abstract to verify the articles were germane to our objective. We then applied filters and conducted consensus meetings to confirm that the articles met the study criteria.

Results

Review of 2224 studies resulted in a final group of 30 articles for analysis. mHealth initiatives were used extensively worldwide for applications such as maternal health, prenatal care, infant care, HIV/AIDS prevention, treatment adherence, cardiovascular disease, diabetes, and health education. Studies were conducted in several developing countries in Africa, Asia, and Latin America. From each article, we recorded the specific health outcome that was improved, mHealth technology used, and barriers to the successful implementation of the intervention in a developing country. The most prominent health outcomes improved with mHealth were infectious diseases and maternal health, accounting for a combined 20/30 (67%) of the total studies in the analysis. The most frequent mHealth technology used was SMS, accounting for 18/30 (60%) of the studies. We identified 73 individual barriers and grouped them into 14 main categories. The top 3 barrier categories were infrastructure, lack of equipment, and technology gap, which together accounted for 28 individual barriers.

Conclusions

This systematic review shed light on the most prominent health outcomes that can be improved using mHealth technology interventions in developing countries. The barriers identified will provide leaders of future intervention projects a solid foundation for their design, thus increasing the chances for long-term success. We suggest that, to overcome the top three barriers, project leaders who wish to implement mHealth interventions must establish partnerships with local governments and nongovernmental organizations to secure funding, leadership, and the required infrastructure.

The implementation of integrated disease surveillance and response in Liberia after Ebola virus disease outbreak 2015-2017

INTRODUCTION

Although Liberia adapted the integrated diseases surveillance and response (IDSR) in 2004 as a platform for implementation of International Health Regulation (IHR (2005)), IDSR was not actively implemented until 2015. Some innovations and best practices were observed during the implementation of IDSR in Liberia after Ebola virus disease outbreak. This paper describes the different approaches used for implementation of IDSR in Liberia from 2015 to 2017.

METHODS

We conducted a cross-sectional study using the findings from IDSR supervisions conducted from September to November 2017 and perused the outbreaks linelists submitted by the counties to the national level from January to December 2017 and key documents available at the national level.

RESULTS

In 2017, the country piloted the use of mobile phones application to store and send data from the health facilities to the national level. In addition, an electronic platform for acute flaccid paralysis (AFP) surveillance called Auto-Visual AFP Detection and Reporting (AVADAR) was piloted in Montserrado County during the first semester of 2017. The timeliness and completeness of reports submitted from the counties to national level were above the target of 80% stable despite the challenges like insufficient resources, including skilled staff.

CONCLUSION

IDSR is being actively implemented in Liberia since 2015. Although the country is facing the same challenges as other countries during the early stages of implementation of IDSR, the several innovations were implemented in a short time. The surveillance system reveled to be resilient, despite the challenges.

Design Choices for Automated Disease Surveillance in the Social Web

The social web has emerged as a dominant information architecture accelerating technology innovation on an unprecedented scale. The utility of these developments to public health use cases like disease surveillance, information dissemination, outbreak prediction and so forth has been widely investigated and variously demonstrated in work spanning several published experimental studies and deployed systems. In this paper we provide an overview of automated disease surveillance efforts based on the social web characterized by their different high level design choices regarding functional aspects like user participation and language parsing approaches. We briefly discuss the technical rationale and practical implications of these different choices in addition to the key limitations associated with these systems within the context of operable disease surveillance. We hope this can offer some technical guidance to multi-disciplinary teams on how best to implement, interpret and evaluate disease surveillance programs based on the social web.

Mobile health solutions in developing countries: a stakeholder perspective

Infrastructural deficiencies, limited access to medical care, and shortage of health care workers are just a few of the barriers to health care in developing countries. mHealth has the potential to overcome at least some of these challenges. To address this, a stakeholder perspective is adopted and an analysis of existing research is undertaken to look at mHealth delivery in developing countries. This study focuses on four key stakeholder groups i.e., health care workers, patients, system developers, and facilitators. A systematic review identifies 108 peer-reviewed articles, which are analysed to determine the extent these articles investigate the different types of stakeholder interactions, and to identify high-level themes emerging within these interactions. This analysis illustrates two key gaps. First, while interactions involving health care workers and/or patients have received significant attention, little research has looked at the role of patient-to-patient interactions. Second, the interactions between system developers and the other stakeholder groups are strikingly under-represented.

Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya

BACKGROUND

The correct knowledge of standard case definition is necessary for frontline health workers to diagnose suspected diseases across Africa. However, surveillance evaluations commonly assume this prerequisite. This study assessed the knowledge of case definitions for health workers and their supervisors for disease surveillance activities in rural Kenya.

METHODS

A cross-sectional survey including 131 health workers and their 11 supervisors was undertaken in two counties in Kenya. Descriptive analysis was conducted to classify the correctness of knowledge into four categories for three tracer diseases (dysentery, measles, and dengue). We conducted a univariate and multivariable logistic regression analyses to explore factors influencing knowledge of the case definition for dysentery.

RESULTS

Among supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. Correct knowledge was observed for 50.4% of the health workers for dysentery, only 12.2% for measles, and none for dengue. Of 10 examined factors, the following were significantly associated with health workers' correct knowledge of the case definition for dysentery: health workers' cadre (aOR 2.71; 95% CI 1.20-6.12; p = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01-4.98; p = 0.048). Health workers' exposure to the surveillance refresher training, supportive supervision and guidelines were not significantly associated with the knowledge.

CONCLUSION

The correct knowledge of standard case definitions was sub-optimal among health workers and their supervisors, which is likely to impact the reliability of routine surveillance reports generated from health facilities.

Understanding mSOS: A qualitative study examining the implementation of a text-messaging outbreak alert system in rural Kenya

Outbreaks of epidemic diseases pose serious public health risks. To overcome the hurdles of sub-optimal disease surveillance reporting from the health facilities to relevant authorities, the Ministry of Health in Kenya piloted mSOS (mobile SMS-based disease outbreak alert system) in 2013-2014. In this paper, we report the results of the qualitative study, which examined factors that influence the performances of mSOS implementation. In-depth interviews were conducted with 11 disease surveillance coordinators and 32 in-charges of rural health facilities that took part in the mSOS intervention. Drawing from the framework analysis, dominant themes that emerged from the interviews are presented. All participants voiced their excitement in using mSOS. The results showed that the technology was well accepted, easy to use, and both health workers and managers unanimously recommended the scale-up of the system despite challenges encountered in the implementation processes. The most challenging components were the context in which mSOS was implemented, including the lack of strong existing structure for continuous support supervision, feedback and response action related to disease surveillance. The study revealed broader health systems issues that should be addressed prior to and during the intervention scale-up.