{"paper_id":"4d8dc415-e0d8-4946-a2f1-1ca28d24990f","body_text":"Comparative analysis of the use of mobile applications versus other reporting channels for adverse events reporting during COVID-19 vaccine deployment in Ghana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative analysis of the use of mobile applications versus other reporting channels for adverse events reporting during COVID-19 vaccine deployment in Ghana Jeremiah Ewudzie-Sampson, Delese Mimi Darko, Seth Kwaku Seaneke, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7234872/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background The novel nature of COVID-19 vaccines and their deployment in an emergency setting in Ghana required the establishment of a well-established pharmacovigilance structure that supports timely identification of safety issues that may compromise public health and safety. The Med Safety App was identified as a tool which could enable a two-way communication between the regulatory body and healthcare professionals or consumers to ensure the monitoring of vaccine safety. Objectives The objective of this study is to perform a comparative analysis of the effectiveness of the Med Safety App for reporting of AEFI compared to other reporting tools during the rollout of COVID-19 vaccines in Ghana. Methodology The study was cross-sectional in design, using mainly primary quantitative data. Additionally, secondary data on reported AEFIs were also reviewed. A quantitative descriptive analysis was conducted on 4,389 spontaneous AEFI reports from COVID-19 vaccines deployed in Ghana from March 2021 to December 2022 to assess the timeliness of reporting and case detection rates defined as number of AEFIs identified per 100,000 surviving infants in a population, for the different tools for reporting AEFIs. A 30-item self-administered questionnaire was administered to 147 healthcare workers to assess their awareness of the Med Safety App for reporting AEFIs during the COVID-19 vaccination. Results Comparatively, 68.2% AEFIs received through the App were reported within 0–3 days compared to 67.3%, 57.4% and 3.1% for SafetyWatch, telephone calls and AEFI paper reporting form respectively for the same period. Majority of healthcare professionals (128, 87.0%) had not heard of the Med Safety App. For a preferred tool for reporting AEFI, telephone (30.82%), paper forms (29.5%), Med Safety App (28.0%), WhatsApp (4.8%), SafetyWatch System (2.7%); 4.1% had no preference for any of the reporting tools. Conclusion The App was found to be very useful in terms of timeliness for reporting and identification of AEFIs by healthcare professionals. However, there was low awareness of the use of the App among healthcare professionals in Ghana. Med Safety App Adverse events following immunization healthcare professionals spontaneous reporting pharmacovigilance BACKGROUND Vaccine pharmacovigilance is a requisite for all immunization programs as this helps sustain public confidence in vaccines 1 . Adverse reactions are identified during the drug and vaccine development process; however, a complete safety profile of a medicinal product can only be obtained during real-world use. This is due to the limitation of the preclinical and clinical studies during the drug development process, including small sample size, short duration of study and homogenous characteristics of study participants. 2 . On 12 January 2020, the World Health Organization (WHO) confirmed that the novel coronavirus was the cause of a respiratory illness in a cluster of people in Wuhan City, Hubei Province, China 3 . There was the need to develop vaccines to mitigate the infections or reduce the severity of disease outcomes, especially in the face of emerging and re-emerging pathogens. The government of Ghana introduced COVID-19 vaccination in March 2021 in line with global strategy to control COVID-19. As of 18th January 2022, a total of 9.3 million of vaccine doses have been administered to 17.5 million eligible population with 15.7% of the people completing primary schedule in Ghana 4 . The rapid development of the COVID-19 vaccines on novel platforms followed by their rapid deployment on a mass scale poses unique challenges for its safety monitoring. Timely detection and reporting of adverse events following COVID-19 immunization was the first step in the continuous verification of vaccine safety 5 . Globally, AEFIs could be reported through paper forms, telephone calls and web-based online forms. 6 . In Ghana, AEFIs are reported via paper reporting forms, telephone calls and an online web-based portal (The SafetyWatch System) and the Med Safety App. In 2019, the Med Safety App was launched in Ghana as an additional electronic platform to the existing reporting tools for reporting safety issues of medicines and vaccines. Although all these platforms have been available for reporting, underreporting continues to be a challenge even during the COVID-19 vaccine deployment. Since its launch, the Med Safety App has been widely promoted for use for reporting adverse reactions since July 2019 due to its immense benefits 7 . The Med Safety App allows users to access safety related news articles and alerts from a country’s national health products regulator, view global safety data of all registered medicines and vaccines in their country, and to create a watch list of products of interest and most importantly report adverse reactions from medicines and vaccines 7 . Due to the novelty of the COVID-19 vaccines in Ghana, it was important to have well established pharmacovigilance procedures to help detect signals and other vaccine related events to safeguard public health and safety. Therefore, it was empirical that tools used in safety monitoring of the vaccines should support quick detection and response to AEFIs and other vaccine related events. Despite the identified potential benefits of the use of the Med Safety App for the monitoring of adverse reactions, its uptake had not been encouraging (National Pharmacovigilance Center, Safety Monitoring Department, FDA Ghana, database). This poses a threat to the quick identification and swift response to AEFIs that have the potential to undermine the COVID-19 vaccination (National Pharmacovigilance Center, Safety Monitoring Department, FDA Ghana, database). Additionally, this has the potential to affect safety monitoring and role of potential vaccines of public health interest, such as the Malaria vaccine (RTS,S) and HIV vaccines. The study was aimed at carrying out comparative analysis of the different reporting channels in terms of reporting rate and timeliness for reporting AEFI after vaccination to establish the uniqueness of the Med Safety App for quick detection of AEFIs or identify a suitable channel applicable in Ghana for safety monitoring of vaccines during vaccination programs especially involving novel vaccines like COVID-19 vaccines. METHODOLOGY Study design The study was cross-sectional in design, using mainly primary quantitative data. Additionally, secondary data on reported AEFI were reviewed. Review of secondary data on reported AEFIs A quantitative descriptive analysis and inferential analysis were conducted on 4,389 spontaneous AEFI reports from COVID-19 vaccines deployed in Ghana from March 2021 to December 2022 to assess the timeliness of reporting and case detection rates defined as number of AEFIs identified per 100,000 surviving infants in a population, for the different tools for reporting. The data consisted of serious and non-serious AEFI reports from five COVID-19 vaccines deployed in Ghana, namely, AZ Covishield, Sputnik V, Moderna, Covid-19 Vaccine Janssen and Pfizer-BioNTech) received at Food and Drugs Authority, Ghana between March 2021 and December 2022. All AEFI reports received at the FDA through the passive reporting pathway for COVID-19 were included. AEFI reports received through active monitoring, i.e cohort event monitoring (CEM) were excluded. Cross sectional study Participants for the cross-sectional survey comprised public health nurses, general nurses, midwives and disease control officers selected from Tema Metropolitan and Ga North Municipal Health Directorates of the Ghana Health Services in the Greater Accra Region. Sampling and sample size determination A total of 147 healthcare professionals were interviewed during a survey to assess the awareness of the use of the Med Safety App for reporting AEFIs in Ghana. Healthcare professionals who were encountered during data collection at the health facilities visited within the district were interviewed. The sample size for the survey was determined using the Cochran sample size formula 8 . Cochran’s formula was used because it is preferable in a scenario where a sample of any given size may be required to provide more information about a smaller population than a larger one. Where; e is the desired level of precision/ acceptable sampling error (i.e. the margin of error), e = 0.05 p is the (estimated) proportion of the population that has the attribute in question, p = 0.1 q is 1 – p, q = 0.9, confidence interval of 95%, Z = 1.96 $$\\:n=\\frac{1.962\\:\\left(0.1\\right)0.9}{{0.005}^{2}}$$ n = 138 A 30-item novel self-administered structured questionnaire developed using Google Forms was administered to participants; this was adapted from a study by Mehmeti et al., 2017). The Participants’ consent was obtained prior to the filling of the questionnaire with objectives of the study clearly explained to the participant (Ewudzie-Sampson 2023, Unpublished manuscript). The questionnaire consisted of four sections: Demographic characteristics : age, sex and place of residency and educational level. Professional experience : information on the type of healthcare professional, length of service as a healthcare worker and experience about vaccination. General knowledge of AEFIs and AEFI reporting in Ghana : to assess level of awareness of healthcare professionals about AEFIs vaccines and vaccines related AEFIs. Awareness of the use of the Med Safety App for reporting AEFI : focused on assessing the level of awareness for healthcare professionals on the use of the Med Safety App for reporting AEFIs and other reporting channels for reporting AEFIs. The knowledge of the definition of an AEFI by the healthcare professionals was assessed by providing them two options as the definition of an AEFI. For option “A”, an AEFI was defined as “any untoward medical events that follow immunization, and that do not necessarily have a causal relationship with the immunization” and option “B, “any untoward medical events that follow immunization which is caused by a vaccine after vaccination”. Per WHO, option “A” is the correct definition of an AEFI.’ Inclusion criteria The survey involved public health nurses, disease control officers and nurses/ midwives in the Tema Municipal and Ga North Municipal Health Directorates in Greater Accra Region. Exclusion criteria Public health nurses, disease control officers, nurses/ midwives who were unwilling to participate in the survey were excluded. Only participants in the selected area were enrolled due to cost and convenience. Only healthcare professionals who were present at work at the time of the data collection were included; those who were absent at the time were not included. Data Analysis The quantitative data obtained from the survey was downloaded as a Microsoft Excel 2016 spreadsheet and cleaned to ensure accurate analysis. Analysis of data was done using Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC; 2019. For the secondary data, reporting rates of AEFI was calculated by age groups, sex, vaccine types, and reaction categories for the different reporting tool used 10 . AEFI reporting rates was calculated using doses administered as denominators. Doses administered provided a more accurate comparison of AEFI reporting rates. The reporting rate was calculated to assess trends among the reporting channels relative to the Med Safety App. Timeliness was estimated by finding the difference between the day of reporting of AEFI by the vaccinee/ healthcare professional to the NPV Center and the onset of the AEFI. 11 In order to establish case detection rate for the various channels as part of the sensitivity measure, the study adopted the recommended WHO case detection rate of 10 per 100,000 surviving infants since there was no peculiar established rate for only the COVID-19 vaccination globally 11 . This was obtained by using the total dose administered as denominator. RESULTS Characteristics of reported AEFIs The highest number of reports were received through the SafetyWatch System (n = 1557, 35.48%), representing a reporting rate of 6.9/100,0000 followed by telephone calls (n = 1473, 33.56%) representing a rate of 6.6/ 100,000 doses administered. Table 1 compares the number of reports and reporting rates of AEFIs received through all the reporting channels and the other variables of interest. There was a significant relationship between the type of reporter and the preferred tool for reporting (Pearson chi2 = 1.7e + 03 Pr = 0.000). The minimum and maximum ages of reporters were 15 and 92 years respectively with a mean age of 36.1 years (± 12.54). The quantum of cases reported through all the channels reduced with increasing age. Overall, 40.2% of AEFIs were received from reporters within 26–35 years. The average number of days between onset of an AEFI and receipt of a report at the FDA was 15 days (± 34.76). Majority of reports were received within the first 3 days after onset of AEFI. The longest time taken before reporting an AEFI was 433 days which relates to over a year after onset of administration of COVID-19 vaccine. Table 1 presents the number of days taken for a reporter to report an AEFI and the timeliness of reporting per channel as compared to the Med Safety App. Most of the reports (40.5%) were received within 0–3 days after vaccination predominately through telephone calls (n = 710, 57.5%). The second highest period of receipt of reports was between 8–21 days (n = 832). These were completed AEFI paper forms filled by healthcare professionals and forwarded to the FDA. In terms of timeliness, the SafetyWatch System was the second most used channel of reporting within the 0–3 days after onset of AEFI; it represented 30.5% of reports received within the period. Table 3 outlines the reporting days and the contribution of the various reporting channels. Comparatively, 68.2% (n = 114) of the 167 AEFIs (which could be used to assess timeliness) received through the App were reported within 0–3 days compared to 67.3%, 57.4% and 3.1% for SafetyWatch, telephone calls and AEFI paper reporting form respectively. The highest number of AEFI reports accounting for 2,784 (63.4%) of AEFIs were received from healthcare professionals. The healthcare professionals included Disease Control Officers, pharmacists, physicians, public health nurses, doctors among others. The reporter type for 812 (18.5%) reports were not provided. It was observed that consumers preferred a faster means of reporting AEFI (Table 1 ). Out of the 793 reports received from the general public, telephone calls was the highest channel of reporting AEFI (56.9%) followed by SafetyWatch System (31.8%). For the 2,784 reports from healthcare professionals, most were reported using the SafetyWatch System (41.0%) followed by AEFI paper forms (40.2%) as compared to the telephone (14.5%) and the Med Safety (4.2%). A Chi square analysis (Pearson chi2(3) = 77.4184 Pr = 0.000) established a significant relationship between the type of reporter and the choice of reporting channel Detection of Serious AEFI per reporting tool For the period considered, 60 serious AEFIs were recorded for all the vaccines with AZ Covishield contributing 61.7% followed by Pfizer, Janssen and Moderna with 20%, 15% respectively (Table 1 ). Twenty (20) cases could be assessed for the time difference between date of onset of the serious AEFI and the date of receipt of the report at the NPV Center. Only one report of serious AEFI was received through the MSA. However, the number of days taken to report could not be ascertained because of incomplete data; Table 1 provides the contribution of the reporting channels in detecting serious AEFIs. Out of the 60 cases, 55%, 23.3% and 20% were reported using the AEFI Paper forms and SafetyWatch System and telephone respectively. Case detection rate The SafetyWatch System had the highest case detection rate of 7 /100,000 doses administered as compared to 0.9/100.000 for the MSA. This was followed by telephone call and AEFI Paper reporting form with rates of 6.6/100,000 and 5.1/100,000 respectively (Table 1 ). Table 1 Demographic distribution of AEFIs per reporting channels Variable Channels for reporting (n,%) MSA AEFI Paper form SafetyWatch System Telephone call Total Sex Male 109(51.7) 805(51.7) 683(46.4) 651(56.7) 2,248 Female 97(46.0) 744(47.8) 790(53.6) 497(43.3) 2128 Not stated 5(2.3) 8(0.5) 0 (0.0) 0(0.0) 13 Age 15–25 28(18.2) 159(14.4) 181(14.3) 200 (16.5) 568 26–35 77(50.0) 578(52.5) 625(49.0) 483(39.9) 1,763 36–45 28(18.2) 205(18.6) 253(19.8) 227(18.7) 713 46–55 11(7.1) 64(5.8) 94(7.4) 126(10.4) 295 56–65 5(3.2) 60(5.4) 83(6.5) 113(9.3) 261 66+ 5(3.2) 35(3.2) 40(3.1) 62(5.1) 142 Not stated 647 Timeliness of reporting (Days to reporting of AEFI after Onset) 0–3 34 (2.8) 114 (9.2) 377 (30.5) 710 (57.5) 1,235 4–7 198 (45.0) 16 (3.6) 81 (18.4) 145 (32.9) 440 8–21 540 (64.9) 14 (1.6) 57 (6.9) 221 (26.6) 832 22–28 153 (82.3) 10 (5.3) 4 (2.2) 19 (10.2) 186 >28 158 (44.5) 13 (3.7) 41 (11.5) 143 (40.3) 355 Type of reporter Consumer/ General public 89(42.2) 0(0.0) 252(16.2) 452(30.7) 793 Healthcare professional 119(56.4) 1120(97.6) 1142(73.3) 403(27.4) 2,784 Not stated 3(1.4) 28(2.4) 163(10.5) 618(41.9) 812 Reaction type and channel for reporting Serious 1(1.7) 33(55.0) 14(23.3) 12(20.0) 60 Non serious 210(4.9) 1115(25.8) 1543(35.6) 1461(33.7) 4,329 Case detection rate per (10/100,000) 0.6 5.1 7.0 6.6 Total doses administered 22,384,226 Survey on awareness of Med Safety App among healthcare professionals Demographics and professional characteristics of participants. One hundred and forty-seven (147) healthcare professionals comprising of disease control officers (6.12%), public health nurses (76.87%) and general nurses/ midwives (17.01%) within the Tema Metropolitan Health Directorate and the Ga West Municipal Health Directorate responded to the survey. The distribution of the professionals is indicated in Table 2 . The mean age of healthcare professionals interviewed was 34.3 years (± 5.3) and 88.4% of respondents were females. Table 2 provides demographics of the healthcare professionals interviewed. Majority of the professionals were between 30 and 40 years. The respondents were mostly public health nurses who administer vaccines during vaccination with their education level ranging from certificate to degree. The level of education of the healthcare professionals is presented in Table 2 . Table 2 Demographic characteristics of healthcare workers in A and B Variable Frequency Percent (%) Sex Female 130 88.4 Male 17 11.6 Age 20–30 39 26.5 31–40 96 65.3 41+ 12 8.2 Profession Disease control officer 9 6.12 General nurse/ midwife 25 17.01 Public health nurse 113 76.87 Level of education Certificate 47 31.9 Degree 38 25.9 Diploma 62 42.2 Years of experience 1–5 51 34.69 6–10 37 25.17 11–15 53 36.05 16 > 6 4.09 Years of practice and awareness of reporting channels Out of the 147 respondents, 65.3% had practiced as healthcare professionals for more than 5 years with mean years of practices of 2.14 years ± 1.1SD. Although 83 (56.46%) of the healthcare professionals interviewed had encountered AEFIs from other vaccines apart from COVID-19 during their practice, 64 (77.1%) reported the AEFI. Out of the 71 respondents who have ever encountered AEFI from COVID-19 vaccines, only 20 (13. 61)% reported using the AEFI paper form. Most of the respondents (80%) were aware of the tools and channels for reporting AEFIs. The AEFI paper reporting form was the most known reporting tool for healthcare professionals. Telephone calls, FDA website and District Health Information and Management System (DHIMS) were some of the channels that the respondents mentioned. However, DHIMS only captures the number of AEFIs received but not the details of the AEFI. Only 4% out of those who did not report COVID-19 AEFIs encountered were not aware of the AEFI reporting channels and the reporting tools; >1% said they did not know who to report to whiles another 1% said they usually manage the AEFI for the clients without reporting. . Awareness of the Med Safety App Majority of healthcare professionals (87.0%, 128) had not heard of the Med Safety App; 9.2% of 19 participants who have heard of the App only got to know of the App during the COVID-19 vaccine deployment; 3 (2.4%) knew about the Med Safety App before the COVID-19 vaccination started in Ghana. Out of the 19 respondents who have heard of the App, only 2 (10.5%) had used the App to report an AEFI; 89.5% of those who know the App used the AEFI paper reporting forms and telephone calls when they reported AEFIs from COVID-19 vaccines instead of the App. To establish the utility of the App, those who had ever heard of the App were asked about the use of the App; 11, (57.9%) of the respondents asserted that “it is used for reporting AEFI from COVID-19 vaccines”, 6 (31.6%) stated it was for “reporting adverse drug reactions”. 1 (5.3%) claimed it was for “receiving safety alerts and information on COVID-19 vaccines”. Although most HCPs were not aware of the Med Safety App, about 28.1% of the respondents preferred the use of the App for reporting AEFI as shown in Table 3 . Those who chose Med Safety over the other reporting channels indicated that the Med Safety App will be a faster and convenient way of reporting an AEFI. However, their challenge was the official order of report submission in the Ghana Health Service (GHS). In the GHS, AEFI reports received are required to be forwarded to the District Health Directorate by the disease control officers who act as field supervisors or contact persons by the public health nurses when they encounter any AEFI. The district disease control officer or EPI coordinator is required to forward the report to GHS national before the report finally gets to the FDA for causality analysis and decision taking. Additionally, 11 out of 19 respondents who have downloaded the App said they will recommend the App to others. When the respondents were asked what will prevent them from using an App for reporting an AEFI, 47.0% indicated that poor internet connectivity may be the major hindrance to the use of the App as against 26.3% and 21.1% ascribing their failure to use the App to cost of data/ internet charges and memory size of the App respectively. Challenges and motivation to use mobile applications Poor internet connectivity was identified as the top reason to ward off the use of a mobile application for reporting AEFIs; this was asserted by 47.3% of the respondents followed by 26.3% and 21.1% linking the cost of internet data and App memory size respectively as the reason for not using the App. Table 3 shows the preferred channels of reporting by respondents and barriers that may prevent them from using the App. Table 3 Preferred channels for AEFI reporting Variable Frequency Percent (%) Preferred tool for Reporting AEFI FDA WhatsApp line 7 4.79 None 7 4.11 Online via FDA website 4 2.74 Paper reporting form at a health facility 43 29.45 Telephone call 45 30.82 The Med Safety App 41 28.08 What will prevent you from using the Med Safety App for reporting AEFI? Cost of data/ internet charges 5 26.3 It may occupy a big memory size on my phone 4 21.1 Poor internet connectivity 9 47.3 None 1 5.2 Bureaucracies in reporting pathways for AEFIs in Ghana Health Services was a challenge to the use of the App. However, when asked about what may motivate the use of a mobile application for reporting, the respondents gave the underlisted reasons; mobile applications are fast and convenient means of reporting. It helps to monitor communication between the FDA and reporters. The Med Safety App was good for follow up since the completed forms will always be available on the App. Mobile applications may give fast notification and prompt action. The App gives direct feedback. DISCUSSION Use of mobile technology for improved AEFI reporting rate The adoption of digital technologies for immunization and public health campaigns have proved to be beneficial for daily activity monitoring. Particularly, the use of mobile information technology supports the collection of standardized data for real-time decision-making during vaccination campaigns. Electronic data collection has been proposed as a solution to many challenges faced by paper-based surveys and is increasingly being adopted in a number of public health programmes 12 . In Ghana it has been noted that, the use of contemporary technology could simplify AEFI reporting. A study by Yamoah et al., in 2019, indicated that online computer programs improved AEFI reporting more than paper forms which many study participants found to be inconvenient. Reporting of adverse reactions of medicines by using an App was identified to offer a unique added value compared to conventional reporting tools, such as paper-based forms. It helped in efficient data collection and management 14 . In the survey conducted for this study only 28.1% alluded to the use of an App as a preferred tool for reporting AEFI. They indicated that the App was a fast and convenient means of reporting AEFIs. The assessment on the preferred choice for reporting AEFI did not bring out any outstanding channel of preference as anticipated; 30.82% and 29.45% preferred the use of the telephone and the AEFI paper reporting respectively. This outcome could be attributed to lack of sensitization on the use of the App for reporting AEFI. From the study, it could be deduced that the utilization of any of the reporting channels was linked to the underlisted factors: Understanding of what is an AEFIs by healthcare professionals and the general public/ consumers. level of awareness about the reporting channels i.e., who to report to and how to report. availability and accessibility of the tool or channel to use for reporting AEFI. reporting practices of healthcare workers and consumers. The general public used the Med Safety App more than healthcare professionals. This contradicted a study by Seaneke et al., 2023 where more healthcare professionals used the the App for reporting adverse events. A study in Uganda showed that training of healthcare professionals promotes proficiency and use of the Med Safety App and efforts should be made to make it an integral training topic. The study also suggested that sufficient training on the App would supports a culture of adverse reaction reporting among Ugandan health workers 15 . In this study, the healthcare professionals were used to the SafetyWatch System and AEFI paper reporting forms during COVID-19 vaccine deployment. The use of the SafetyWatch System may be due to sensitization of some few healthcare professionals who were aware of the web based online reporting channel (SafetyWatch System) as part of stimulated passive and active surveillance strategies. The survey proved that most healthcare professionals were only aware of the AEFI paper reporting form and not any other reporting channel; their awareness of the other reporting channels was very low. The knowledge of the use and the availability of the AEFI paper reporting form was a positive outcome for AEFI surveillance in Ghana. However, the bureaucratic processes involved and the length of days in their transmission to the FDA may adversely affect timely receipt of reports and the deployment of necessary intervention for public health intervention especially during campaign or emergency situations. The Med Safety App recorded the lowest reporting rate of 0.9 per 100,000 doses administered. However, it performed highly in terms of timeliness of reporting, which indicates the swift nature of the App in providing safety updates on immunization programmes as envisaged. A recent study in Burkina Faso supports the swiftness of receiving adverse reactions from COVID-19 treatment medications by the regulatory compared to paper reporting forms 16 . More consumers reported through the App within 0–3 days of onset of the AEFI as compared to the other reporting channels. This could be explained by increasing access to smart phones where App could be downloaded and used. A survey by the National Communication Authority, Ghana in 2020 showed that 54.1% of individuals, aged five years and older, own a functional mobile phone. On average, more individuals own basic phones (47.9%) and smartphones (46.1%) as compared to feature phones (12.8%) 17 . In a study by Fukushima et al., 2022b, feedback received from respondents showed that apps make adverse reaction reporting accessible to a broader population since anyone with a smartphone can download the app and report . Wilson et al., 2016 in their research on improving vaccine registries through mobile technologies concluded that timely and accurate flow of information regarding immunization has enormous value for vaccinees, public health officials and industry. They noted that the emergence of mobile technologies poses an opportunity to address gaps within existing data management systems. In another by Di Filippo et al. in 2022, the findings alluded to the fact that an adaptable and widespread technology, such as a mobile App, can be used to raise the ADR-reporting rate by leveraging active involvement of the general public. The study assessed the usefulness of an App named vaxEffect@UniMiB and asserted that the App was an effective combination to assure high response rates in circumstances where much information on a product is not available, but sound decisions made quickly. AEFI knowledge disparity between public health and clinical practice Limited understanding of adverse events following immunization (AEFI) contributes significantly to their underreporting. General nurses and midwives were found to have less knowledge of AEFI and the appropriate reporting channels compared to public health nurses, highlighting a critical gap in surveillance capacity and the risk of missing AEFI cases. General nurses and midwives are the clinical interphase in the public health system. Ideally, clinicians, nurses, midwives, physician assistants are required to probe any patient especially children between age 0–60 months of receipt of vaccine within the last 7 days as part of the procedure for diagnosis. This is same for vaccine recipients during any vaccination campaign such as the COVID-19 vaccination. A lack of knowledge of what an AEFI is and the channel for reporting is an indictment on the sensitivity of Ghana’s AEFI surveillance. More attention on training and awareness on AEFI is focused on public health cadre of staff of the Ghana’s health system rather than those in clinical practice. Generally, the healthcare professionals, especially the public health nurses and the disease control officers understood what an AEFI however the tendency to report was low. Barriers to the use of the Med Safety App Fukushima et al., 2022b in the conclusion of their study stated that, although a feature of the mobile application they assessed enabled the use of some functions without an internet connection, it required internet connectivity to subsequently transmit the information. Respondents in countries with limited internet connectivity reported persistent difficulties in using the apps. This confirms concerns raised by the healthcare professionals as a reason for not using the Med Safety App. Inadequate knowledge about AEFIs and low level of awareness on the use of the App was a major challenge. In a study by Barnor (2002), he concluded that majority of health professionals could not adequately define an AEFI according to the WHO Guideline on AEFI. He identified education and enhanced awareness creation about AEFIs as a potential to promote reporting in Ghana. In another study by Mehmeti et al., in 2017, they also asserted that though healthcare professionals may know what an AEFI is, they may not have good reporting habit or as much understanding of the players in vaccination safety and the AEFI surveillance process; this ultimately affects AEFI surveillance and reporting. In this study, it was realized that disease control officers and the public health nurses who a major player in immunization in Ghana had adequate knowledge of AEFI and the use of the AEFI paper form as a channel for reporting. However, attitude towards reporting was low. Most of them did not report AEFIs they encountered because of the COVID-19 vaccines or other vaccines. Another challenge to the use of the Med Safety App and other electronic means of reporting was bureaucratic procedures for submission of AEFI report in the Ghana Health Service (GHS). This affects timely response to safety issues or concerns during vaccination programs. Per the order, AEFI reports received are required to be forwarded to the District Health Directorate by the disease control officers who act as field supervisors or contact persons for the public health nurses/vaccinator when they encounter any AEFI. The district disease control officer or EPI coordinator is required to forward the report to GHS national before the report finally gets to the FDA for causality assessment and decision taking. This promotes the use of paper reporting forms since they serve as good evidence of reporting for operational and administrative purposes. Limitations to the study The major limitation to this study was inability to assess the awareness level of consumers which made it impossible to establish their level of familiarity with the various AEFI reporting channels in Ghana. Accessibility to clinicians for this was very difficult; this would have provided a wider and wholistic view of the level of understanding and awareness of the AEFI reporting channels by all cadre of the healthcare delivery system in Ghana. The low numbers of spontaneous AEFI reports received through the Med Safety App affected the strength of analysis. Incomplete data for some reporting channels may impact representation of use of the various reporting channels. Further research could be carried out with a focus on awareness of consumers and clinicians about Med Safety App and the other reporting channels used in AEFI surveillance. Strength of the study Despite the limitations outlined, the results on timeliness for reporting adverse reactions with of the App suggests the capacity of the App to help identify safety issues with regards to vaccines in any vaccination activity. Additionally, the outcome of analysis of the primary data collected during the survey among healthcare professionals could be used to implement strategies to improve the awareness and the use of the Med Safety App for reporting AEFI in Ghana. CONCLUSION Despite these undesirable outcomes, the usefulness of the App cannot be overemphasized; it showed clearly as the best tool for surveillance on AEFI and vaccines related events in terms of timeliness in the receipt of report. The App supports a real time reporting of events which will ultimately contribute to timely intervention by the Food and Drugs Authority and the other collaborating stakeholders in the immunization programmes in any case of vaccine related events (VREs). The responses from the survey showed that the AEFI paper reporting tool was widely known and used by healthcare professionals which proved positive for AEFI detection. However, it should be promoted as a last resort for reporting AEFIs both in routine and campaign scenarios. From the study, it can be deduced that the use of the Med Safety App has the potential to improve rate of reporting of AEFIs because it supports timely reporting to the FDA compared to the other reporting channels. This will help in rapid respond to serious AEFIs and other vaccine related events during immunization programmes. Declarations Acknowledgement The authors would like to thank all members of the SAVING Consortium funded by EDCTP, participants, and others who were involved directly or indirectly during data collection and reviewed this manuscript. Ethical consideration The research protocol was reviewed and approved by the Ghana Health Service Ethics Committee with reference number GHS-ERC: 038/12/22 before the commencement of the survey. An approval letter was obtained from the FDA for the use of the COVID-19 vaccines AEFI for the secondary data analysis. All participants gave informed consent to participate in the study. The research was conducted in accordance with the principles of the Declaration of Helsinki (2013 version). Consent for publication Not applicable. Availability of data and materials The data collected and analyzed during the study is available from the author upon reasonable request. Contact, Jeremiah Ewudzie-Sampson (corresponding author) via email, [email protected] . Declaration of conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article Competing interest The authors have no affiliations or financial indulgence with any organization or entity with financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancy, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties. Funding This study was funded by the EDCTP through the SAVING Consortium, Grant No:- CSA2018HS-2528. References WHO. Global Manual on Surveillance of Adverse Events Following Immunization. Angew Chemie Int Ed 6(11), 951–952 (2021) ; 2013–2015 Gao Z, Yang Y, Meng R et al (2022) Automatic assessment of adverse drug reaction reports with interactive visual exploration. Sci Rep 12:1–11 Lake MA (2020) What we know so far: COVID-19 current clinical knowledge and research. Clin Med J R Coll Physicians Lond 20:124–127 Nonvignon J, Owusu R, Asare B et al (2022) Estimating the cost of COVID-19 vaccine deployment and introduction in Ghana using the CVIC tool. Vaccine 40:1879–1887 Ahmed S, Iqbal J, Sadiq K et al (2022) Association of Anti-Rotavirus IgA Seroconversion with Growth, Environmental Enteric Dysfunction and Enteropathogens in Rural Pakistani Infants. Vaccine 40:3444–3451 World Health Organization. Immunization Safety Surveillance:Guidelines for immunization programme managers on surveillance of adverse events following immunization. Third edition. WHO Reg Off West Pacific (2016) ; 1–169 Seaneke SK, Darko DM, Nkansah E et al First results from the lessons learnt from the deployment of the Med Safety App for reporting adverse drug reactions in Ghana. Digit Heal ; 9. Epub ahead of print 2023. 10.1177/20552076231211276 Uakarn C (2021) Sample size estimation using Yamane and Cochran and Krejcie and Morgan and Green formulas and Cohen statistical power analysis by G*power and comparisons. Apheit Int J 10:76–88 Mehmeti I, Nelaj E, Simaku A et al (2017) Knowledge, practice and approaches of health professionals to adverse events following immunization and their reporting in Albania. Heliyon 3:e00331 Ontario PH Trends Constantine M, Cremance T, Juru TP et al (2018) Evaluation of the adverse events following immunization surveillance system in Guruve District, Mashonaland central 2017. Pan Afr Med J 31:1–10 UNICEF. The Use of Digital Technologies and Approaches for Real-Time Monitoring of Supplementary Immunization Activities Good practices and lessons learned (2021) ; 78 Yamoah P, Bangalee V, Oosthuizen F (2019) Knowledge and perceptions of adverse events following immunization among healthcare professionals in Africa: A case study from Ghana. Vaccines 7:1–15 Fukushima A, Iessa N, Balakrishnan MR et al (2022) Smartphone-based mobile applications for adverse drug reactions reporting: global status and country experience. BMC Med Inf Decis Mak 22:1–20 Kiguba R, Zakumumpa H, Ndagije HB et al (2023) Facilitators and Barriers to Uptake of the Med Safety Mobile App for Adverse Drug Reaction Reporting by Health Workers in Uganda: A Qualitative Study. Drug Saf 46:565–574 Ouoba J, Haro-Lankoandé S, Nacoulma AP et al (2024) Evaluation of the Med Safety mobile app for reporting adverse events in Burkina Faso. Drugs Ther Perspect 40:330–339 National Communication Authority (2019) Quarterly Statistical Bulletin on Communications in Ghana. Natl Commun Auth 4:1–50 Fukushima A, Iessa N, Balakrishnan MR et al (2022) Smartphone-based mobile applications for adverse drug reactions reporting: global status and country experience. BMC Med Inf Decis Mak 22:1–26 Wilson K, Atkinson KM, Deeks SL et al (2016) Improving vaccine registries through mobile technologies: A vision for mobile enhanced Immunization information systems. J Am Med Inf Assoc 23:207–211 Di Filippo M, Avellone A, Belingheri M et al A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability Study. JMIR Hum Factors ; 9. Epub ahead of print 2022. 10.2196/38701 Additional Declarations No competing interests reported. Supplementary Files Questionnaire.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 04 Oct, 2025 Reviewers agreed at journal 01 Oct, 2025 Reviewers invited by journal 18 Sep, 2025 Editor assigned by journal 12 Sep, 2025 Editor invited by journal 11 Aug, 2025 Submission checks completed at journal 11 Aug, 2025 First submitted to journal 11 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Adverse reactions are identified during the drug and vaccine development process; however, a complete safety profile of a medicinal product can only be obtained during real-world use. This is due to the limitation of the preclinical and clinical studies during the drug development process, including small sample size, short duration of study and homogenous characteristics of study participants. \\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eOn 12 January 2020, the World Health Organization (WHO) confirmed that the novel coronavirus was the cause of a respiratory illness in a cluster of people in Wuhan City, Hubei Province, China \\u003csup\\u003e\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e. There was the need to develop vaccines to mitigate the infections or reduce the severity of disease outcomes, especially in the face of emerging and re-emerging pathogens. The government of Ghana introduced COVID-19 vaccination in March 2021 in line with global strategy to control COVID-19. As of 18th January 2022, a total of 9.3\\u0026nbsp;million of vaccine doses have been administered to 17.5\\u0026nbsp;million eligible population with 15.7% of the people completing primary schedule in Ghana \\u003csup\\u003e\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eThe rapid development of the COVID-19 vaccines on novel platforms followed by their rapid deployment on a mass scale poses unique challenges for its safety monitoring. Timely detection and reporting of adverse events following COVID-19 immunization was the first step in the continuous verification of vaccine safety \\u003csup\\u003e\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e. Globally, AEFIs could be reported through paper forms, telephone calls and web-based online forms. \\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e. In Ghana, AEFIs are reported via paper reporting forms, telephone calls and an online web-based portal (The SafetyWatch System) and the Med Safety App. In 2019, the Med Safety App was launched in Ghana as an additional electronic platform to the existing reporting tools for reporting safety issues of medicines and vaccines. Although all these platforms have been available for reporting, underreporting continues to be a challenge even during the COVID-19 vaccine deployment. Since its launch, the Med Safety App has been widely promoted for use for reporting adverse reactions since July 2019 due to its immense benefits \\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e. The Med Safety App allows users to access safety related news articles and alerts from a country\\u0026rsquo;s national health products regulator, view global safety data of all registered medicines and vaccines in their country, and to create a watch list of products of interest and most importantly report adverse reactions from medicines and vaccines \\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eDue to the novelty of the COVID-19 vaccines in Ghana, it was important to have well established pharmacovigilance procedures to help detect signals and other vaccine related events to safeguard public health and safety. Therefore, it was empirical that tools used in safety monitoring of the vaccines should support quick detection and response to AEFIs and other vaccine related events. Despite the identified potential benefits of the use of the Med Safety App for the monitoring of adverse reactions, its uptake had not been encouraging (National Pharmacovigilance Center, Safety Monitoring Department, FDA Ghana, database). This poses a threat to the quick identification and swift response to AEFIs that have the potential to undermine the COVID-19 vaccination (National Pharmacovigilance Center, Safety Monitoring Department, FDA Ghana, database). Additionally, this has the potential to affect safety monitoring and role of potential vaccines of public health interest, such as the Malaria vaccine (RTS,S) and HIV vaccines.\\u003c/p\\u003e\\u003cp\\u003eThe study was aimed at carrying out comparative analysis of the different reporting channels in terms of reporting rate and timeliness for reporting AEFI after vaccination to establish the uniqueness of the Med Safety App for quick detection of AEFIs or identify a suitable channel applicable in Ghana for safety monitoring of vaccines during vaccination programs especially involving novel vaccines like COVID-19 vaccines.\\u003c/p\\u003e\"},{\"header\":\"METHODOLOGY\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStudy design\\u003c/h2\\u003e\\u003cp\\u003eThe study was cross-sectional in design, using mainly primary quantitative data. Additionally, secondary data on reported AEFI were reviewed.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eReview of secondary data on reported AEFIs\\u003c/h3\\u003e\\n\\u003cp\\u003eA quantitative descriptive analysis and inferential analysis were conducted on 4,389 spontaneous AEFI reports from COVID-19 vaccines deployed in Ghana from March 2021 to December 2022 to assess the timeliness of reporting and case detection rates defined as number of AEFIs identified per 100,000 surviving infants in a population, for the different tools for reporting. The data consisted of serious and non-serious AEFI reports from five COVID-19 vaccines deployed in Ghana, namely, AZ Covishield, Sputnik V, Moderna, Covid-19 Vaccine Janssen and Pfizer-BioNTech) received at Food and Drugs Authority, Ghana between March 2021 and December 2022. All AEFI reports received at the FDA through the passive reporting pathway for COVID-19 were included. AEFI reports received through active monitoring, i.e cohort event monitoring (CEM) were excluded.\\u003c/p\\u003e\\n\\u003ch3\\u003eCross sectional study\\u003c/h3\\u003e\\n\\u003cp\\u003eParticipants for the cross-sectional survey comprised public health nurses, general nurses, midwives and disease control officers selected from Tema Metropolitan and Ga North Municipal Health Directorates of the Ghana Health Services in the Greater Accra Region.\\u003c/p\\u003e\\n\\u003ch3\\u003eSampling and sample size determination\\u003c/h3\\u003e\\n\\u003cp\\u003eA total of 147 healthcare professionals were interviewed during a survey to assess the awareness of the use of the Med Safety App for reporting AEFIs in Ghana. Healthcare professionals who were encountered during data collection at the health facilities visited within the district were interviewed. The sample size for the survey was determined using the Cochran sample size formula \\u003csup\\u003e\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e\\u003c/sup\\u003e. Cochran\\u0026rsquo;s formula was used because it is preferable in a scenario where a sample of any given size may be required to provide more information about a smaller population than a larger one.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eWhere;\\u003c/p\\u003e\\u003cp\\u003ee is the desired level of precision/ acceptable sampling error (i.e. the margin of error), e\\u0026thinsp;=\\u0026thinsp;0.05\\u003c/p\\u003e\\u003cp\\u003ep is the (estimated) proportion of the population that has the attribute in question, p\\u0026thinsp;=\\u0026thinsp;0.1\\u003c/p\\u003e\\u003cp\\u003eq is 1 \\u0026ndash; p, q\\u0026thinsp;=\\u0026thinsp;0.9, confidence interval of 95%, Z\\u0026thinsp;=\\u0026thinsp;1.96\\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:n=\\\\frac{1.962\\\\:\\\\left(0.1\\\\right)0.9}{{0.005}^{2}}$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003en\\u0026thinsp;=\\u0026thinsp;138\\u003c/p\\u003e\\u003cp\\u003eA 30-item novel self-administered structured questionnaire developed using Google Forms was administered to participants; this was adapted from a study by Mehmeti et al., 2017). The Participants\\u0026rsquo; consent was obtained prior to the filling of the questionnaire with objectives of the study clearly explained to the participant (Ewudzie-Sampson 2023, Unpublished manuscript).\\u003c/p\\u003e\\u003cp\\u003eThe questionnaire consisted of four sections:\\u003c/p\\u003e\\u003cp\\u003e\\u003cul\\u003e\\u003cli\\u003e\\u003cp\\u003e\\u003cem\\u003eDemographic characteristics\\u003c/em\\u003e: age, sex and place of residency and educational level.\\u003c/p\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cp\\u003e\\u003cem\\u003eProfessional experience\\u003c/em\\u003e: information on the type of healthcare professional, length of service as a healthcare worker and experience about vaccination.\\u003c/p\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cp\\u003e\\u003cem\\u003eGeneral knowledge of AEFIs and AEFI reporting in Ghana\\u003c/em\\u003e: to assess level of awareness of healthcare professionals about AEFIs vaccines and vaccines related AEFIs.\\u003c/p\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cp\\u003e\\u003cem\\u003eAwareness of the use of the Med Safety App for reporting AEFI\\u003c/em\\u003e: focused on assessing the level of awareness for healthcare professionals on the use of the Med Safety App for reporting AEFIs and other reporting channels for reporting AEFIs.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/ul\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe knowledge of the definition of an AEFI by the healthcare professionals was assessed by providing them two options as the definition of an AEFI. For option \\u0026ldquo;A\\u0026rdquo;, an AEFI was defined as \\u0026ldquo;any untoward medical events that follow immunization, and that do not necessarily have a causal relationship with the immunization\\u0026rdquo; and option \\u0026ldquo;B, \\u0026ldquo;any untoward medical events that follow immunization which is caused by a vaccine after vaccination\\u0026rdquo;. Per WHO, option \\u0026ldquo;A\\u0026rdquo; is the correct definition of an AEFI.\\u0026rsquo;\\u003c/p\\u003e\\n\\u003ch3\\u003eInclusion criteria\\u003c/h3\\u003e\\n\\u003cp\\u003eThe survey involved public health nurses, disease control officers and nurses/ midwives in the Tema Municipal and Ga North Municipal Health Directorates in Greater Accra Region.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eExclusion criteria\\u003c/h2\\u003e\\u003cp\\u003ePublic health nurses, disease control officers, nurses/ midwives who were unwilling to participate in the survey were excluded. Only participants in the selected area were enrolled due to cost and convenience. Only healthcare professionals who were present at work at the time of the data collection were included; those who were absent at the time were not included.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eData Analysis\\u003c/h2\\u003e\\u003cp\\u003eThe quantitative data obtained from the survey was downloaded as a Microsoft Excel 2016 spreadsheet and cleaned to ensure accurate analysis. Analysis of data was done using Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC; 2019.\\u003c/p\\u003e\\u003cp\\u003eFor the secondary data, reporting rates of AEFI was calculated by age groups, sex, vaccine types, and reaction categories for the different reporting tool used \\u003csup\\u003e\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u003c/sup\\u003e. AEFI reporting rates was calculated using doses administered as denominators. Doses administered provided a more accurate comparison of AEFI reporting rates. The reporting rate was calculated to assess trends among the reporting channels relative to the Med Safety App.\\u003c/p\\u003e\\u003cp\\u003eTimeliness was estimated by finding the difference between the day of reporting of AEFI by the vaccinee/ healthcare professional to the NPV Center and the onset of the AEFI. \\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e\\u003cp\\u003eIn order to establish case detection rate for the various channels as part of the sensitivity measure, the study adopted the recommended WHO case detection rate of 10 per 100,000 surviving infants since there was no peculiar established rate for only the COVID-19 vaccination globally \\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e. This was obtained by using the total dose administered as denominator.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"RESULTS\",\"content\":\"\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eCharacteristics of reported AEFIs\\u003c/h2\\u003e\\u003cp\\u003eThe highest number of reports were received through the SafetyWatch System (n\\u0026thinsp;=\\u0026thinsp;1557, 35.48%), representing a reporting rate of 6.9/100,0000 followed by telephone calls (n\\u0026thinsp;=\\u0026thinsp;1473, 33.56%) representing a rate of 6.6/ 100,000 doses administered. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e compares the number of reports and reporting rates of AEFIs received through all the reporting channels and the other variables of interest. There was a significant relationship between the type of reporter and the preferred tool for reporting (Pearson chi2\\u0026thinsp;=\\u0026thinsp;1.7e\\u0026thinsp;+\\u0026thinsp;03 Pr\\u0026thinsp;=\\u0026thinsp;0.000). The minimum and maximum ages of reporters were 15 and 92 years respectively with a mean age of 36.1 years (\\u0026plusmn;\\u0026thinsp;12.54). The quantum of cases reported through all the channels reduced with increasing age. Overall, 40.2% of AEFIs were received from reporters within 26\\u0026ndash;35 years. The average number of days between onset of an AEFI and receipt of a report at the FDA was 15 days (\\u0026plusmn;\\u0026thinsp;34.76). Majority of reports were received within the first 3 days after onset of AEFI.\\u003c/p\\u003e\\u003cp\\u003eThe longest time taken before reporting an AEFI was 433 days which relates to over a year after onset of administration of COVID-19 vaccine. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e presents the number of days taken for a reporter to report an AEFI and the timeliness of reporting per channel as compared to the Med Safety App. Most of the reports (40.5%) were received within 0\\u0026ndash;3 days after vaccination predominately through telephone calls (n\\u0026thinsp;=\\u0026thinsp;710, 57.5%). The second highest period of receipt of reports was between 8\\u0026ndash;21 days (n\\u0026thinsp;=\\u0026thinsp;832). These were completed AEFI paper forms filled by healthcare professionals and forwarded to the FDA. In terms of timeliness, the SafetyWatch System was the second most used channel of reporting within the 0\\u0026ndash;3 days after onset of AEFI; it represented 30.5% of reports received within the period. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e outlines the reporting days and the contribution of the various reporting channels. Comparatively, 68.2% (n\\u0026thinsp;=\\u0026thinsp;114) of the 167 AEFIs (which could be used to assess timeliness) received through the App were reported within 0\\u0026ndash;3 days compared to 67.3%, 57.4% and 3.1% for SafetyWatch, telephone calls and AEFI paper reporting form respectively.\\u003c/p\\u003e\\u003cp\\u003eThe highest number of AEFI reports accounting for 2,784 (63.4%) of AEFIs were received from healthcare professionals. The healthcare professionals included Disease Control Officers, pharmacists, physicians, public health nurses, doctors among others. The reporter type for 812 (18.5%) reports were not provided. It was observed that consumers preferred a faster means of reporting AEFI (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Out of the 793 reports received from the general public, telephone calls was the highest channel of reporting AEFI (56.9%) followed by SafetyWatch System (31.8%). For the 2,784 reports from healthcare professionals, most were reported using the SafetyWatch System (41.0%) followed by AEFI paper forms (40.2%) as compared to the telephone (14.5%) and the Med Safety (4.2%). A Chi square analysis (Pearson chi2(3)\\u0026thinsp;=\\u0026thinsp;77.4184 Pr\\u0026thinsp;=\\u0026thinsp;0.000) established a significant relationship between the type of reporter and the choice of reporting channel\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eDetection of Serious AEFI per reporting tool\\u003c/h2\\u003e\\u003cp\\u003eFor the period considered, 60 serious AEFIs were recorded for all the vaccines with AZ Covishield contributing 61.7% followed by Pfizer, Janssen and Moderna with 20%, 15% respectively (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Twenty (20) cases could be assessed for the time difference between date of onset of the serious AEFI and the date of receipt of the report at the NPV Center. Only one report of serious AEFI was received through the MSA. However, the number of days taken to report could not be ascertained because of incomplete data; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e provides the contribution of the reporting channels in detecting serious AEFIs. Out of the 60 cases, 55%, 23.3% and 20% were reported using the AEFI Paper forms and SafetyWatch System and telephone respectively.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eCase detection rate\\u003c/h2\\u003e\\u003cp\\u003eThe SafetyWatch System had the highest case detection rate of 7 /100,000 doses administered as compared to 0.9/100.000 for the MSA. This was followed by telephone call and AEFI Paper reporting form with rates of 6.6/100,000 and 5.1/100,000 respectively (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eDemographic distribution of AEFIs per reporting channels\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eVariable\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c6\\\" namest=\\\"c2\\\"\\u003e\\u003cp\\u003eChannels for reporting (n,%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMSA\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eAEFI Paper form\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eSafetyWatch System\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eTelephone call\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eTotal\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e109(51.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e805(51.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e683(46.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e651(56.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2,248\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e97(46.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e744(47.8)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e790(53.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e497(43.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2128\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot stated\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5(2.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e8(0.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0(0.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e13\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAge\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e15\\u0026ndash;25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e28(18.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e159(14.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e181(14.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e200 (16.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e568\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e26\\u0026ndash;35\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e77(50.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e578(52.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e625(49.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e483(39.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1,763\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e36\\u0026ndash;45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e28(18.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e205(18.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e253(19.8)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e227(18.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e713\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e46\\u0026ndash;55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e11(7.1)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e64(5.8)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e94(7.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e126(10.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e295\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e56\\u0026ndash;65\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5(3.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e60(5.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e83(6.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e113(9.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e261\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e66+\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5(3.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e35(3.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e40(3.1)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e62(5.1)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e142\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot stated\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e647\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eTimeliness of reporting (Days to reporting of AEFI after Onset)\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e0\\u0026ndash;3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e34 (2.8)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e114 (9.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e377 (30.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e710 (57.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1,235\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e4\\u0026ndash;7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e198 (45.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e16 (3.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e81 (18.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e145 (32.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e440\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e8\\u0026ndash;21\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e540 (64.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e14 (1.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e57 (6.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e221 (26.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e832\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e22\\u0026ndash;28\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e153 (82.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e10 (5.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e4 (2.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e19 (10.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e186\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026gt;28\\u003c/p\\u003e \\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e158 (44.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e13 (3.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e41 (11.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e143 (40.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e355\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eType of reporter\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eConsumer/ General public\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e89(42.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0(0.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e252(16.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e452(30.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e793\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHealthcare professional\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e119(56.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1120(97.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1142(73.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e403(27.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2,784\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot stated\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e3(1.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e28(2.4)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e163(10.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e618(41.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e812\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReaction type and channel for reporting\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSerious\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1(1.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e33(55.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e14(23.3)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e12(20.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNon serious\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e210(4.9)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1115(25.8)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1543(35.6)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1461(33.7)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e4,329\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eCase detection rate per (10/100,000)\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e7.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e6.6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eTotal doses administered\\u003c/strong\\u003e\\u003cp\\u003e22,384,226\\u003c/p\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eSurvey on awareness of Med Safety App among healthcare professionals\\u003c/h2\\u003e\\u003cp\\u003e\\u003cb\\u003eDemographics and professional characteristics of participants.\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003eOne hundred and forty-seven (147) healthcare professionals comprising of disease control officers (6.12%), public health nurses (76.87%) and general nurses/ midwives (17.01%) within the Tema Metropolitan Health Directorate and the Ga West Municipal Health Directorate responded to the survey. The distribution of the professionals is indicated in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\u003cp\\u003eThe mean age of healthcare professionals interviewed was 34.3 years (\\u0026plusmn;\\u0026thinsp;5.3) and 88.4% of respondents were females. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e provides demographics of the healthcare professionals interviewed. Majority of the professionals were between 30 and 40 years. The respondents were mostly public health nurses who administer vaccines during vaccination with their education level ranging from certificate to degree. The level of education of the healthcare professionals is presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eDemographic characteristics of healthcare workers in A and B\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariable\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercent (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e130\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e88.4\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e17\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e11.6\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAge\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e20\\u0026ndash;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e39\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e31\\u0026ndash;40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e96\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e65.3\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e41+\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e8.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eProfession\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDisease control officer\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e6.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGeneral nurse/ midwife\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e17.01\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePublic health nurse\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e113\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e76.87\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eLevel of education\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCertificate\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e47\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e31.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDegree\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e38\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDiploma\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e62\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e42.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eYears of experience\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u0026ndash;5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e51\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e34.69\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e6\\u0026ndash;10\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e37\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e11\\u0026ndash;15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e53\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e36.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e16 \\u0026gt;\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.09\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eYears of practice and awareness of reporting channels\\u003c/h2\\u003e\\u003cp\\u003eOut of the 147 respondents, 65.3% had practiced as healthcare professionals for more than 5 years with mean years of practices of 2.14 years\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.1SD. Although 83 (56.46%) of the healthcare professionals interviewed had encountered AEFIs from other vaccines apart from COVID-19 during their practice, 64 (77.1%) reported the AEFI. Out of the 71 respondents who have ever encountered AEFI from COVID-19 vaccines, only 20 (13. 61)% reported using the AEFI paper form. Most of the respondents (80%) were aware of the tools and channels for reporting AEFIs.\\u003c/p\\u003e\\u003cp\\u003eThe AEFI paper reporting form was the most known reporting tool for healthcare professionals. Telephone calls, FDA website and District Health Information and Management System (DHIMS) were some of the channels that the respondents mentioned. However, DHIMS only captures the number of AEFIs received but not the details of the AEFI. Only 4% out of those who did not report COVID-19 AEFIs encountered were not aware of the AEFI reporting channels and the reporting tools; \\u0026gt;1% said they did not know who to report to whiles another 1% said they usually manage the AEFI for the clients without reporting. .\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eAwareness of the Med Safety App\\u003c/h2\\u003e\\u003cp\\u003eMajority of healthcare professionals (87.0%, 128) had not heard of the Med Safety App; 9.2% of 19 participants who have heard of the App only got to know of the App during the COVID-19 vaccine deployment; 3 (2.4%) knew about the Med Safety App before the COVID-19 vaccination started in Ghana. Out of the 19 respondents who have heard of the App, only 2 (10.5%) had used the App to report an AEFI; 89.5% of those who know the App used the AEFI paper reporting forms and telephone calls when they reported AEFIs from COVID-19 vaccines instead of the App.\\u003c/p\\u003e\\u003cp\\u003eTo establish the utility of the App, those who had ever heard of the App were asked about the use of the App; 11, (57.9%) of the respondents asserted that \\u0026ldquo;it is used for reporting AEFI from COVID-19 vaccines\\u0026rdquo;, 6 (31.6%) stated it was for \\u0026ldquo;reporting adverse drug reactions\\u0026rdquo;. 1 (5.3%) claimed it was for \\u0026ldquo;receiving safety alerts and information on COVID-19 vaccines\\u0026rdquo;.\\u003c/p\\u003e\\u003cp\\u003eAlthough most HCPs were not aware of the Med Safety App, about 28.1% of the respondents preferred the use of the App for reporting AEFI as shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e. Those who chose Med Safety over the other reporting channels indicated that the Med Safety App will be a faster and convenient way of reporting an AEFI. However, their challenge was the official order of report submission in the Ghana Health Service (GHS). In the GHS, AEFI reports received are required to be forwarded to the District Health Directorate by the disease control officers who act as field supervisors or contact persons by the public health nurses when they encounter any AEFI. The district disease control officer or EPI coordinator is required to forward the report to GHS national before the report finally gets to the FDA for causality analysis and decision taking.\\u003c/p\\u003e\\u003cp\\u003eAdditionally, 11 out of 19 respondents who have downloaded the App said they will recommend the App to others. When the respondents were asked what will prevent them from using an App for reporting an AEFI, 47.0% indicated that poor internet connectivity may be the major hindrance to the use of the App as against 26.3% and 21.1% ascribing their failure to use the App to cost of data/ internet charges and memory size of the App respectively.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eChallenges and motivation to use mobile applications\\u003c/h2\\u003e\\u003cp\\u003ePoor internet connectivity was identified as the top reason to ward off the use of a mobile application for reporting AEFIs; this was asserted by 47.3% of the respondents followed by 26.3% and 21.1% linking the cost of internet data and App memory size respectively as the reason for not using the App. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e shows the preferred channels of reporting by respondents and barriers that may prevent them from using the App.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003ePreferred channels for AEFI reporting\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariable\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercent (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePreferred tool for Reporting AEFI\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFDA WhatsApp line\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.79\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNone\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.11\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOnline via FDA website\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e2.74\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePaper reporting form at a health facility\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e43\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e29.45\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTelephone call\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e30.82\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eThe Med Safety App\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e28.08\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eWhat will prevent you from using the Med Safety App for reporting AEFI?\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCost of data/ internet charges\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26.3\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eIt may occupy a big memory size on my phone\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e21.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePoor internet connectivity\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e47.3\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNone\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eBureaucracies in reporting pathways for AEFIs in Ghana Health Services was a challenge to the use of the App. However, when asked about what may motivate the use of a mobile application for reporting, the respondents gave the underlisted reasons;\\u003c/p\\u003e\\u003cp\\u003e\\u003col\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003emobile applications are fast and convenient means of reporting.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eIt helps to monitor communication between the FDA and reporters.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eThe Med Safety App was good for follow up since the completed forms will always be available on the App.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eMobile applications may give fast notification and prompt action.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eThe App gives direct feedback.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003c/ol\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"DISCUSSION\",\"content\":\"\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eUse of mobile technology for improved AEFI reporting rate\\u003c/h2\\u003e\\u003cp\\u003eThe adoption of digital technologies for immunization and public health campaigns have proved to be beneficial for daily activity monitoring. Particularly, the use of mobile information technology supports the collection of standardized data for real-time decision-making during vaccination campaigns. Electronic data collection has been proposed as a solution to many challenges faced by paper-based surveys and is increasingly being adopted in a number of public health programmes \\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u003c/sup\\u003e. In Ghana it has been noted that, the use of contemporary technology could simplify AEFI reporting. A study by Yamoah et al., in 2019, indicated that online computer programs improved AEFI reporting more than paper forms which many study participants found to be inconvenient.\\u003c/p\\u003e\\u003cp\\u003eReporting of adverse reactions of medicines by using an App was identified to offer a unique added value compared to conventional reporting tools, such as paper-based forms. It helped in efficient data collection and management \\u003csup\\u003e\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u003c/sup\\u003e. In the survey conducted for this study only 28.1% alluded to the use of an App as a preferred tool for reporting AEFI. They indicated that the App was a fast and convenient means of reporting AEFIs. The assessment on the preferred choice for reporting AEFI did not bring out any outstanding channel of preference as anticipated; 30.82% and 29.45% preferred the use of the telephone and the AEFI paper reporting respectively. This outcome could be attributed to lack of sensitization on the use of the App for reporting AEFI. From the study, it could be deduced that the utilization of any of the reporting channels was linked to the underlisted factors:\\u003c/p\\u003e\\u003cp\\u003e\\u003col\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eUnderstanding of what is an AEFIs by healthcare professionals and the general public/ consumers.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003elevel of awareness about the reporting channels i.e., who to report to and how to report.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003eavailability and accessibility of the tool or channel to use for reporting AEFI.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003cspan\\u003e\\u003cli\\u003e\\u003cp\\u003ereporting practices of healthcare workers and consumers.\\u003c/p\\u003e\\u003c/li\\u003e\\u003c/span\\u003e\\u003c/ol\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe general public used the Med Safety App more than healthcare professionals. This contradicted a study by Seaneke et al., 2023 where more healthcare professionals used the the App for reporting adverse events. A study in Uganda showed that training of healthcare professionals promotes proficiency and use of the Med Safety App and efforts should be made to make it an integral training topic. The study also suggested that sufficient training on the App would supports a culture of adverse reaction reporting among Ugandan health workers \\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e. In this study, the healthcare professionals were used to the SafetyWatch System and AEFI paper reporting forms during COVID-19 vaccine deployment. The use of the SafetyWatch System may be due to sensitization of some few healthcare professionals who were aware of the web based online reporting channel (SafetyWatch System) as part of stimulated passive and active surveillance strategies. The survey proved that most healthcare professionals were only aware of the AEFI paper reporting form and not any other reporting channel; their awareness of the other reporting channels was very low.\\u003c/p\\u003e\\u003cp\\u003eThe knowledge of the use and the availability of the AEFI paper reporting form was a positive outcome for AEFI surveillance in Ghana. However, the bureaucratic processes involved and the length of days in their transmission to the FDA may adversely affect timely receipt of reports and the deployment of necessary intervention for public health intervention especially during campaign or emergency situations.\\u003c/p\\u003e\\u003cp\\u003eThe Med Safety App recorded the lowest reporting rate of 0.9 per 100,000 doses administered. However, it performed highly in terms of timeliness of reporting, which indicates the swift nature of the App in providing safety updates on immunization programmes as envisaged. A recent study in Burkina Faso supports the swiftness of receiving adverse reactions from COVID-19 treatment medications by the regulatory compared to paper reporting forms \\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e. More consumers reported through the App within 0\\u0026ndash;3 days of onset of the AEFI as compared to the other reporting channels. This could be explained by increasing access to smart phones where App could be downloaded and used. A survey by the National Communication Authority, Ghana in 2020 showed that 54.1% of individuals, aged five years and older, own a functional mobile phone. On average, more individuals own basic phones (47.9%) and smartphones (46.1%) as compared to feature phones (12.8%) \\u003csup\\u003e\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u003c/sup\\u003e. In a study by Fukushima et al., 2022b, feedback received from respondents showed that apps make adverse reaction reporting accessible to a broader population since anyone with a smartphone can download the app and report .\\u003c/p\\u003e\\u003cp\\u003eWilson et al., 2016 in their research on improving vaccine registries through mobile technologies concluded that timely and accurate flow of information regarding immunization has enormous value for vaccinees, public health officials and industry. They noted that the emergence of mobile technologies poses an opportunity to address gaps within existing data management systems. In another by Di Filippo et al. in 2022, the findings alluded to the fact that an adaptable and widespread technology, such as a mobile App, can be used to raise the ADR-reporting rate by leveraging active involvement of the general public. The study assessed the usefulness of an App named vaxEffect@UniMiB and asserted that the App was an effective combination to assure high response rates in circumstances where much information on a product is not available, but sound decisions made quickly.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eAEFI knowledge disparity between public health and clinical practice\\u003c/h2\\u003e\\u003cp\\u003eLimited understanding of adverse events following immunization (AEFI) contributes significantly to their underreporting. General nurses and midwives were found to have less knowledge of AEFI and the appropriate reporting channels compared to public health nurses, highlighting a critical gap in surveillance capacity and the risk of missing AEFI cases. General nurses and midwives are the clinical interphase in the public health system. Ideally, clinicians, nurses, midwives, physician assistants are required to probe any patient especially children between age 0\\u0026ndash;60 months of receipt of vaccine within the last 7 days as part of the procedure for diagnosis. This is same for vaccine recipients during any vaccination campaign such as the COVID-19 vaccination. A lack of knowledge of what an AEFI is and the channel for reporting is an indictment on the sensitivity of Ghana\\u0026rsquo;s AEFI surveillance. More attention on training and awareness on AEFI is focused on public health cadre of staff of the Ghana\\u0026rsquo;s health system rather than those in clinical practice. Generally, the healthcare professionals, especially the public health nurses and the disease control officers understood what an AEFI however the tendency to report was low.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eBarriers to the use of the Med Safety App\\u003c/h2\\u003e\\u003cp\\u003eFukushima et al., 2022b in the conclusion of their study stated that, although a feature of the mobile application they assessed enabled the use of some functions without an internet connection, it required internet connectivity to subsequently transmit the information. Respondents in countries with limited internet connectivity reported persistent difficulties in using the apps. This confirms concerns raised by the healthcare professionals as a reason for not using the Med Safety App.\\u003c/p\\u003e\\u003cp\\u003eInadequate knowledge about AEFIs and low level of awareness on the use of the App was a major challenge. In a study by Barnor (2002), he concluded that majority of health professionals could not adequately define an AEFI according to the WHO Guideline on AEFI. He identified education and enhanced awareness creation about AEFIs as a potential to promote reporting in Ghana. In another study by Mehmeti et al., in 2017, they also asserted that though healthcare professionals may know what an AEFI is, they may not have good reporting habit or as much understanding of the players in vaccination safety and the AEFI surveillance process; this ultimately affects AEFI surveillance and reporting. In this study, it was realized that disease control officers and the public health nurses who a major player in immunization in Ghana had adequate knowledge of AEFI and the use of the AEFI paper form as a channel for reporting. However, attitude towards reporting was low. Most of them did not report AEFIs they encountered because of the COVID-19 vaccines or other vaccines.\\u003c/p\\u003e\\u003cp\\u003eAnother challenge to the use of the Med Safety App and other electronic means of reporting was bureaucratic procedures for submission of AEFI report in the Ghana Health Service (GHS). This affects timely response to safety issues or concerns during vaccination programs. Per the order, AEFI reports received are required to be forwarded to the District Health Directorate by the disease control officers who act as field supervisors or contact persons for the public health nurses/vaccinator when they encounter any AEFI. The district disease control officer or EPI coordinator is required to forward the report to GHS national before the report finally gets to the FDA for causality assessment and decision taking. This promotes the use of paper reporting forms since they serve as good evidence of reporting for operational and administrative purposes.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eLimitations to the study\\u003c/h2\\u003e\\u003cp\\u003eThe major limitation to this study was inability to assess the awareness level of consumers which made it impossible to establish their level of familiarity with the various AEFI reporting channels in Ghana. Accessibility to clinicians for this was very difficult; this would have provided a wider and wholistic view of the level of understanding and awareness of the AEFI reporting channels by all cadre of the healthcare delivery system in Ghana. The low numbers of spontaneous AEFI reports received through the Med Safety App affected the strength of analysis. Incomplete data for some reporting channels may impact representation of use of the various reporting channels. Further research could be carried out with a focus on awareness of consumers and clinicians about Med Safety App and the other reporting channels used in AEFI surveillance.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec23\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eStrength of the study\\u003c/h2\\u003e\\u003cp\\u003eDespite the limitations outlined, the results on timeliness for reporting adverse reactions with of the App suggests the capacity of the App to help identify safety issues with regards to vaccines in any vaccination activity. Additionally, the outcome of analysis of the primary data collected during the survey among healthcare professionals could be used to implement strategies to improve the awareness and the use of the Med Safety App for reporting AEFI in Ghana.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\"},{\"header\":\"CONCLUSION\",\"content\":\"\\u003cp\\u003eDespite these undesirable outcomes, the usefulness of the App cannot be overemphasized; it showed clearly as the best tool for surveillance on AEFI and vaccines related events in terms of timeliness in the receipt of report. The App supports a real time reporting of events which will ultimately contribute to timely intervention by the Food and Drugs Authority and the other collaborating stakeholders in the immunization programmes in any case of vaccine related events (VREs). The responses from the survey showed that the AEFI paper reporting tool was widely known and used by healthcare professionals which proved positive for AEFI detection. However, it should be promoted as a last resort for reporting AEFIs both in routine and campaign scenarios. From the study, it can be deduced that the use of the Med Safety App has the potential to improve rate of reporting of AEFIs because it supports timely reporting to the FDA compared to the other reporting channels. This will help in rapid respond to serious AEFIs and other vaccine related events during immunization programmes.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors would like to thank all members of the SAVING Consortium funded by EDCTP, participants, and others who were involved directly or indirectly during data collection and reviewed this manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cspan id=\\\"_Toc133597999\\\"\\u003eEthical consideration\\u003c/span\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe research protocol was reviewed and approved by the Ghana Health Service Ethics Committee with reference number \\u003cstrong\\u003eGHS-ERC: 038/12/22\\u003c/strong\\u003e before the commencement of the survey. An approval letter was obtained from the FDA for the use of the COVID-19 vaccines AEFI for the secondary data analysis.\\u0026nbsp;All participants gave informed consent to participate in the study. The research was conducted in accordance with the principles of the Declaration of Helsinki (2013 version).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data collected and analyzed during the study is available from the author upon reasonable request. Contact, Jeremiah Ewudzie-Sampson (corresponding author) via email, jeremiah.ewudzie@fda.gov.gh.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of conflicting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors have no affiliations or financial indulgence with any organization or entity with financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancy, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was funded by the EDCTP through the SAVING Consortium, Grant No:- CSA2018HS-2528.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eWHO. Global Manual on Surveillance of Adverse Events Following Immunization. Angew Chemie Int Ed 6(11), 951\\u0026ndash;952 (2021) ; 2013\\u0026ndash;2015\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGao Z, Yang Y, Meng R et al (2022) Automatic assessment of adverse drug reaction reports with interactive visual exploration. Sci Rep 12:1\\u0026ndash;11\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLake MA (2020) What we know so far: COVID-19 current clinical knowledge and research. Clin Med J R Coll Physicians Lond 20:124\\u0026ndash;127\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eNonvignon J, Owusu R, Asare B et al (2022) Estimating the cost of COVID-19 vaccine deployment and introduction in Ghana using the CVIC tool. Vaccine 40:1879\\u0026ndash;1887\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAhmed S, Iqbal J, Sadiq K et al (2022) Association of Anti-Rotavirus IgA Seroconversion with Growth, Environmental Enteric Dysfunction and Enteropathogens in Rural Pakistani Infants. Vaccine 40:3444\\u0026ndash;3451\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWorld Health Organization. Immunization Safety Surveillance:Guidelines for immunization programme managers on surveillance of adverse events following immunization. Third edition. WHO Reg Off West Pacific (2016) ; 1\\u0026ndash;169\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSeaneke SK, Darko DM, Nkansah E et al First results from the lessons learnt from the deployment of the Med Safety App for reporting adverse drug reactions in Ghana. \\u003cem\\u003eDigit Heal\\u003c/em\\u003e; 9. Epub ahead of print 2023. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1177/20552076231211276\\u003c/span\\u003e\\u003cspan address=\\\"10.1177/20552076231211276\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eUakarn C (2021) Sample size estimation using Yamane and Cochran and Krejcie and Morgan and Green formulas and Cohen statistical power analysis by G*power and comparisons. Apheit Int J 10:76\\u0026ndash;88\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMehmeti I, Nelaj E, Simaku A et al (2017) Knowledge, practice and approaches of health professionals to adverse events following immunization and their reporting in Albania. Heliyon 3:e00331\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eOntario PH Trends\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eConstantine M, Cremance T, Juru TP et al (2018) Evaluation of the adverse events following immunization surveillance system in Guruve District, Mashonaland central 2017. Pan Afr Med J 31:1\\u0026ndash;10\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eUNICEF. The Use of Digital Technologies and Approaches for Real-Time Monitoring of Supplementary Immunization Activities Good practices and lessons learned (2021) ; 78\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eYamoah P, Bangalee V, Oosthuizen F (2019) Knowledge and perceptions of adverse events following immunization among healthcare professionals in Africa: A case study from Ghana. Vaccines 7:1\\u0026ndash;15\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFukushima A, Iessa N, Balakrishnan MR et al (2022) Smartphone-based mobile applications for adverse drug reactions reporting: global status and country experience. BMC Med Inf Decis Mak 22:1\\u0026ndash;20\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKiguba R, Zakumumpa H, Ndagije HB et al (2023) Facilitators and Barriers to Uptake of the Med Safety Mobile App for Adverse Drug Reaction Reporting by Health Workers in Uganda: A Qualitative Study. Drug Saf 46:565\\u0026ndash;574\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eOuoba J, Haro-Lankoand\\u0026eacute; S, Nacoulma AP et al (2024) Evaluation of the Med Safety mobile app for reporting adverse events in Burkina Faso. Drugs Ther Perspect 40:330\\u0026ndash;339\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eNational Communication Authority (2019) Quarterly Statistical Bulletin on Communications in Ghana. Natl Commun Auth 4:1\\u0026ndash;50\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFukushima A, Iessa N, Balakrishnan MR et al (2022) Smartphone-based mobile applications for adverse drug reactions reporting: global status and country experience. BMC Med Inf Decis Mak 22:1\\u0026ndash;26\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWilson K, Atkinson KM, Deeks SL et al (2016) Improving vaccine registries through mobile technologies: A vision for mobile enhanced Immunization information systems. J Am Med Inf Assoc 23:207\\u0026ndash;211\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDi Filippo M, Avellone A, Belingheri M et al A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability Study. JMIR Hum Factors ; 9. Epub ahead of print 2022. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.2196/38701\\u003c/span\\u003e\\u003cspan address=\\\"10.2196/38701\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-digital-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [BMC Digital Health](https://bmcdigitalhealth.biomedcentral.com/)\",\"snPcode\":\"44247\",\"submissionUrl\":\"https://submission.nature.com/new-submission/44247/3\",\"title\":\"BMC Digital Health\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Med Safety App, Adverse events following immunization, healthcare professionals, spontaneous reporting, pharmacovigilance\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7234872/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7234872/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eThe novel nature of COVID-19 vaccines and their deployment in an emergency setting in Ghana required the establishment of a well-established pharmacovigilance structure that supports timely identification of safety issues that may compromise public health and safety. The Med Safety App was identified as a tool which could enable a two-way communication between the regulatory body and healthcare professionals or consumers to ensure the monitoring of vaccine safety.\\u003c/p\\u003e\\u003ch2\\u003eObjectives\\u003c/h2\\u003e\\u003cp\\u003eThe objective of this study is to perform a comparative analysis of the effectiveness of the Med Safety App for reporting of AEFI compared to other reporting tools during the rollout of COVID-19 vaccines in Ghana.\\u003c/p\\u003e\\u003ch2\\u003eMethodology\\u003c/h2\\u003e\\u003cp\\u003eThe study was cross-sectional in design, using mainly primary quantitative data. Additionally, secondary data on reported AEFIs were also reviewed. A quantitative descriptive analysis was conducted on 4,389 spontaneous AEFI reports from COVID-19 vaccines deployed in Ghana from March 2021 to December 2022 to assess the timeliness of reporting and case detection rates defined as number of AEFIs identified per 100,000 surviving infants in a population, for the different tools for reporting AEFIs. A 30-item self-administered questionnaire was administered to 147 healthcare workers to assess their awareness of the Med Safety App for reporting AEFIs during the COVID-19 vaccination.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eComparatively, 68.2% AEFIs received through the App were reported within 0\\u0026ndash;3 days compared to 67.3%, 57.4% and 3.1% for SafetyWatch, telephone calls and AEFI paper reporting form respectively for the same period. Majority of healthcare professionals (128, 87.0%) had not heard of the Med Safety App. For a preferred tool for reporting AEFI, telephone (30.82%), paper forms (29.5%), Med Safety App (28.0%), WhatsApp (4.8%), SafetyWatch System (2.7%); 4.1% had no preference for any of the reporting tools.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e\\u003cp\\u003eThe App was found to be very useful in terms of timeliness for reporting and identification of AEFIs by healthcare professionals. However, there was low awareness of the use of the App among healthcare professionals in Ghana.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Comparative analysis of the use of mobile applications versus other reporting channels for adverse events reporting during COVID-19 vaccine deployment in Ghana\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-29 06:28:18\",\"doi\":\"10.21203/rs.3.rs-7234872/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-04T23:21:43+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"176880248743741505995376451792985069519\",\"date\":\"2025-10-02T00:52:05+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-09-18T09:23:47+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-09-12T11:44:58+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-08-11T15:19:47+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-08-11T13:30:38+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Digital Health\",\"date\":\"2025-08-11T13:27:33+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-digital-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [BMC Digital Health](https://bmcdigitalhealth.biomedcentral.com/)\",\"snPcode\":\"44247\",\"submissionUrl\":\"https://submission.nature.com/new-submission/44247/3\",\"title\":\"BMC Digital Health\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"8b635a8b-e3b7-4e85-b76f-2b3c6de16cc8\",\"owner\":[],\"postedDate\":\"September 29th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-09-29T06:28:18+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-29 06:28:18\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7234872\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7234872\",\"identity\":\"rs-7234872\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}