scholarly journals The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study

10.2196/14276 ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. e14276 ◽  
Author(s):  
Myeongchan Kim ◽  
Sehyo Yune ◽  
Seyun Chang ◽  
Yuseob Jung ◽  
Soon Ok Sa ◽  
...  
Keyword(s):  
Health Care Providers ◽  
Surveillance System ◽  
Central Government ◽  
Time Lag ◽  
Target Population ◽  
Mobile App ◽  
Influenza Surveillance ◽  
Care Providers ◽  
Surveillance Network ◽  
Influenza Activity

Background Effective surveillance of influenza requires a broad network of health care providers actively reporting cases of influenza-like illnesses and positive laboratory results. Not only is this traditional surveillance system costly to establish and maintain but there is also a time lag between a change in influenza activity and its detection. A new surveillance system that is both reliable and timely will help public health officials to effectively control an epidemic and mitigate the burden of the disease. Objective This study aimed to evaluate the use of parent-reported data of febrile illnesses in children submitted through the Fever Coach app in real-time surveillance of influenza activities. Methods Fever Coach is a mobile app designed to help parents and caregivers manage fever in young children, currently mainly serviced in South Korea. The app analyzes data entered by a caregiver and provides tailored information for care of the child based on the child’s age, sex, body weight, body temperature, and accompanying symptoms. Using the data submitted to the app during the 2016-2017 influenza season, we built a regression model that monitors influenza incidence for the 2017-2018 season and validated the model by comparing the predictions with the public influenza surveillance data from the Korea Centers for Disease Control and Prevention (KCDC). Results During the 2-year study period, 70,203 diagnosis data, including 7702 influenza reports, were submitted. There was a significant correlation between the influenza activity predicted by Fever Coach and that reported by KCDC (Spearman ρ=0.878; P<.001). Using this model, the influenza epidemic in the 2017-2018 season was detected 10 days before the epidemic alert announced by KCDC. Conclusions The Fever Coach app successfully collected data from 7.73% (207,699/2,686,580) of the target population by providing care instruction for febrile children. These data were used to develop a model that accurately estimated influenza activity measured by the central government agency using reports from sentinel facilities in the national surveillance network.

scholarly journals The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study (Preprint)

2019 ◽  
Author(s):  
Myeongchan Kim ◽  
Sehyo Yune ◽  
Seyun Chang ◽  
Yuseob Jung ◽  
Soon Ok Sa ◽  
...  
Keyword(s):  
Health Care Providers ◽  
Surveillance System ◽  
Central Government ◽  
Time Lag ◽  
Target Population ◽  
Mobile App ◽  
Influenza Surveillance ◽  
Care Providers ◽  
Surveillance Network ◽  
Influenza Activity

BACKGROUND Effective surveillance of influenza requires a broad network of health care providers actively reporting cases of influenza-like illnesses and positive laboratory results. Not only is this traditional surveillance system costly to establish and maintain but there is also a time lag between a change in influenza activity and its detection. A new surveillance system that is both reliable and timely will help public health officials to effectively control an epidemic and mitigate the burden of the disease. OBJECTIVE This study aimed to evaluate the use of parent-reported data of febrile illnesses in children submitted through the Fever Coach app in real-time surveillance of influenza activities. METHODS Fever Coach is a mobile app designed to help parents and caregivers manage fever in young children, currently mainly serviced in South Korea. The app analyzes data entered by a caregiver and provides tailored information for care of the child based on the child’s age, sex, body weight, body temperature, and accompanying symptoms. Using the data submitted to the app during the 2016-2017 influenza season, we built a regression model that monitors influenza incidence for the 2017-2018 season and validated the model by comparing the predictions with the public influenza surveillance data from the Korea Centers for Disease Control and Prevention (KCDC). RESULTS During the 2-year study period, 70,203 diagnosis data, including 7702 influenza reports, were submitted. There was a significant correlation between the influenza activity predicted by Fever Coach and that reported by KCDC (Spearman ρ=0.878; <italic>P</italic>&lt;.001). Using this model, the influenza epidemic in the 2017-2018 season was detected 10 days before the epidemic alert announced by KCDC. CONCLUSIONS The Fever Coach app successfully collected data from 7.73% (207,699/2,686,580) of the target population by providing care instruction for febrile children. These data were used to develop a model that accurately estimated influenza activity measured by the central government agency using reports from sentinel facilities in the national surveillance network.

scholarly journals Pilot study to harmonize the reported influenza intensity levels within the Spanish Influenza Sentinel Surveillance System (SISSS) using the Moving Epidemic Method (MEM)

2016 ◽  
Vol 145 (4) ◽  
pp. 715-722 ◽  
Author(s):  
M. BANGERT ◽  
H. GIL ◽  
J. OLIVA ◽  
C. DELGADO ◽  
T. VEGA ◽  
...  
Keyword(s):  
Pilot Study ◽  
Surveillance System ◽  
Historical Data ◽  
Sentinel Surveillance ◽  
Rank Test ◽  
Influenza Surveillance ◽  
Surveillance Network ◽  
Spanish Influenza ◽  
Influenza Activity ◽  
Sentinel Surveillance System

SUMMARYThe intensity of annual Spanish influenza activity is currently estimated from historical data of the Spanish Influenza Sentinel Surveillance System (SISSS) using qualitative indicators from the European Influenza Surveillance Network. However, these indicators are subjective, based on qualitative comparison with historical data of influenza-like illness rates. This pilot study assesses the implementation of Moving Epidemic Method (MEM) intensity levels during the 2014–2015 influenza season within the 17 sentinel networks covered by SISSS, comparing them to historically reported indicators. Intensity levels reported and those obtained with MEM at the epidemic peak of the influenza wave, and at national and regional levels did not show statistical difference (P = 0·74, Wilcoxon signed-rank test), suggesting that the implementation of MEM would have limited disrupting effects on the dynamic of notification within the surveillance system. MEM allows objective influenza surveillance monitoring and standardization of criteria for comparing the intensity of influenza epidemics in regions in Spain. Following this pilot study, MEM has been adopted to harmonize the reporting of intensity levels of influenza activity in Spain, starting in the 2015–2016 season.

Influenza Surveillance Islamabad and Rawalpindi, Pakistan, September 2017 - February 2018 (Preprint)

2020 ◽  
Author(s):  
Dr Nadia ◽  
Saima Dil ◽  
Naveed Ullah Khan ◽  
Rana Jawad Asghar ◽  
Farida Khudaidad Khan ◽  
...  
Keyword(s):  
Health Care Providers ◽  
Influenza A ◽  
Case Fatality ◽  
Sudden Onset ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Care Providers ◽  
Surveillance Network ◽  
Cross Sectional ◽  
Influenza A H1n1

BACKGROUND Background: Globally 5-10%adults and 20-30%children are affected by influenza annually. Annual epidemics result in 3-5million cases of serious illness and approximately500,000 deaths. In 2008 a sentinel lab-based influenza surveillance network was established in Pakistan in collaboration with CDC having objectives to assess trends of Influenza-like-Illness(ILI) and Severe Acute Respiratory Illness(SARI). OBJECTIVE Objectives: To assess burden of disease, identify risk factors, and recommend control measures. METHODS Methods: A cross-sectional study was conducted based on influenza surveillance data obtained from NICLP from September 2017 to February 2018.Study was done from the data records and samples of suspected ILI patients received from hospitals of Islamabad and Rawalpindi. A case was defined as sudden onset of fever of ≥ 38 C° and cough, with onset within last 10 days. Samples were tested at NICLP for confirmation by RT-PCR. Frequencies were calculated and data analyzed as per time, place and person RESULTS Results: A total of 1500 samples were received out of which 435(29%) were found positive. Among positive samples 246(56.5%) were Influenza-A(H1N1) pdm09,165(38%) were Influenza-A(H3N1) and 24(5.5%) were influenza B.Mean age was 39 years(range 40 days-80 years)while maximum cases were reported from age group 30-39 years(n=77)followed by 50-59 years(n=59).Males were predominant 256(58.8%). Among cases, 21(4.8%) healthcare workers. Travel history was found in 21(4.8%) cases while 35(8%) cases had contact with influenza patients and 14(3.2%) had contact with birds. Among positive cases 262(60%) were reported from Rawalpindi. Majority of cases were reported in January (277) followed by February (112). 31.4% met SARI case definition. Median hospital stay was 5days.During hospitalization 124(26.3%) were ICU admissions, out of them 2(0.42%) were on ventilator, 83(17.6%) were mechanically ventilated. Prevalence of influenza in reported cases was 0.01%.Six confirmed cases died with Case Fatality Rate=1.27%. CONCLUSIONS Conclusion Most cases reported were of Influenza-A (H1N1) pdm09. Based on the results, policy for inclusion of flu vaccination on annual basis is recommended for health care providers and general community.

scholarly journals Mobile Apps for Drug–Drug Interaction Checks in Chinese App Stores: Systematic Review and Content Analysis (Preprint)

2020 ◽  
Author(s):  
Chunying Shen ◽  
Bin Jiang ◽  
Qilian Yang ◽  
Chengnan Wang ◽  
Kevin Z Lu ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Health Care Providers ◽  
Arithmetic Mean ◽  
Mobile App ◽  
Average Score ◽  
Care Providers ◽  
Rating Score ◽  
Average Rating ◽  
Mhealth Apps

BACKGROUND As a computerized drug–drug interaction (DDI) alert system has not been widely implemented in China, health care providers are relying on mobile health (mHealth) apps as references for checking drug information, including DDIs. OBJECTIVE The main objective of this study was to evaluate the quality and content of mHealth apps supporting DDI checking in Chinese app stores. METHODS A systematic review was carried out in November 2020 to identify mHealth apps providing DDI checking in both Chinese iOS and Android platforms. We extracted the apps’ general information (including the developer, operating system, costs, release date, size, number of downloads, and average rating), scientific or clinical basis, and accountability, based on a multidimensional framework for evaluation of apps. The quality of mHealth apps was evaluated by using the Mobile App Rating Scale (MARS). Descriptive statistics, including numbers and percentages, were calculated to describe the characteristics of the apps. For each app selected for evaluation, the section-specific MARS scores were calculated by taking the arithmetic mean, while the overall MARS score was described as the arithmetic mean of the section scores. In addition, the Cohen kappa (κ) statistic was used to evaluate the interrater agreement. RESULTS A total of 7 apps met the selection criteria, and only 3 included citations. The average rating score for Android apps was 3.5, with a minimum of 1.0 and a maximum of 4.9, while the average rating score for iOS apps was 4.7, with a minimum of 4.2 and a maximum of 4.9. The mean MARS score was 3.69 out of 5 (95% CI 3.34-4.04), with the lowest score of 1.96 for Medication Guidelines and the highest score of 4.27 for MCDEX mobile. The greatest variation was observed in the information section, which ranged from 1.41 to 4.60. The functionality section showed the highest mean score of 4.05 (95% CI 3.71-4.40), whereas the engagement section resulted in the lowest average score of 3.16 (95% CI 2.81-3.51). For the information quality section, which was the focus of this analysis, the average score was 3.42, with the MCDEX mobile app having the highest score of 4.6 and the Medication Guidelines app having the lowest score of 1.9. For the overall MARS score, the Cohen interrater κ was 0.354 (95% CI 0.236-0.473), the Fleiss κ was 0.353 (95% CI, 0.234-0.472), and the Krippendorff α was 0.356 (95% CI 0.237-0.475). CONCLUSIONS This study systematically reviewed the mHealth apps in China with a DDI check feature. The majority of investigated apps demonstrated high quality with accurate and comprehensive information on DDIs. However, a few of the apps that had a massive number of downloads in the Chinese market provided incorrect information. Given these apps might be used by health care providers for checking potential DDIs, this creates a substantial threat to patient safety.

scholarly journals Non-invasive prenatal testing: what an obstetrician needs to know

2020 ◽  
Vol 9 (12) ◽  
pp. 5200
Author(s):  
Mishu Mangla
Keyword(s):  
Health Care Providers ◽  
Prenatal Screening ◽  
Prenatal Testing ◽  
High Sensitivity ◽  
Target Population ◽  
Care Providers ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Primary Health Care Providers ◽  
First Choice

No field in obstetrics has seen such fast advancement, as the field of prenatal screening and diagnosis. A wide variety of tests are available today, and this at times becomes confusing both for the patient and the treating doctor that which screening test would be best suited in the given circumstances. Non-invasive prenatal screening, with its numerous advantages is rapidly becoming the test of first choice, especially in the affording set of population.  Although, the test has a very high sensitivity and a very good positive predictive value, this too suffers from some disadvantages which should be clear to the obstetrician ordering the test. A good knowledge about the test, the ideal target population in which this should be offered as the primary screening tool and limitations of the test should be known to all practicing obstetricians and primary health care providers. The current review aims to provide a simplified and updated knowledge regarding non-invasive prenatal testing (NIPT), its major advantages and disadvantages and summarizes the role of ultrasound in patients with negative NIPT.

scholarly journals Geographic Information System enabled dengue surveillance system in south zone, Bangalore city: A pilot study

2021 ◽  
Vol 33 (1) ◽  
pp. 153-160
Author(s):  
Naveen Ramesh ◽  
Venkatesh Thimmaiah ◽  
Shivkumar Mallaiah ◽  
Anasuya Kandaswamy
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Health Care Providers ◽  
Surveillance System ◽  
Geographic Information ◽  
Care Providers ◽  
Entomological Surveillance ◽  
Bangalore City ◽  
South Zone ◽  
Entomological Data

Introduction: The Public Health Information and Epidemiological Cell (PHIEC) of Bruhat Bengaluru Mahanagara Palike (BBMP) utilizes the Geographic Information System (GIS) enabled integrated surveillance for collection, integration, analysis and reporting of geo-referenced epidemiological diseases in Bangalore city. Dengue fever is an emerging disease and there are minimum studies conducted in India about the GIS enabled dengue surveillance system. Objective: To assess the relationship between dengue cases and vector indices as depicted in the GIS map. Methodology: Data regarding dengue confirmed cases was obtained from PHIEC and entomological surveillance data from Urban Primary Health Centres (UPHC) for May to July 2017 in south zone of Bangalore city and active data collection was done for August and September 2017. Results: There was significant association between the number of dengue cases and the Breteau index in the month of September. However, there was no association between vector indices and the number of cases during the month of October. In some wards, contrary findings were noted between dengue vector indices and number of cases reported. Conclusion: There was a relationship between reported dengue cases and vector indices and there is a need for incorporation of entomological data into GIS system along with epidemiological and intervention data. Involvement of more private and government health care providers may help answer the gap between entomological data and number of dengue cases.

Prescribing an App? Oncology Providers’ Views on Mobile Health Apps for Cancer Care

2017 ◽  
pp. 1-7 ◽  
Author(s):  
Callie M. Berkowitz ◽  
Leah L. Zullig ◽  
Bridget F. Koontz ◽  
Sophia K. Smith
Keyword(s):  
Patient Care ◽  
Health Care Providers ◽  
Mobile Health ◽  
Cancer Care ◽  
Structured Interview ◽  
Mobile App ◽  
Care Providers ◽  
Supportive Services ◽  
Wide Range ◽  
Oncology Providers

Introduction Although there are over 500 mobile health (mHealth) applications (apps) available for download in the field of oncology, little research has addressed their acceptability among health care providers. In addition, the providers’ perspectives regarding patient app use has been largely unexamined. We conducted a qualitative study to explore opportunities and barriers for mHealth app use for oncology care. Methods We developed a structured interview guide focusing on acceptability, appropriateness, feasibility, and sustainability of the use of apps in cancer care. We interviewed 15 oncology providers about their attitudes and preferences. De-identified audio recordings were transcribed and coded for emerging themes. Results Providers interviewed included physicians (n = 8) and advanced practice (n = 3) and supportive services (n = 4) providers who care for a wide range of cancer types; ages ranged from 32 to 68 years. Interviews lasted approximately 30 minutes. Oncology providers reported limited exposure to mHealth apps in patient care, but were generally open to recommending or prescribing apps in the future. Key themes included opportunities for mobile app use (including general health promotion, tracking symptoms, and engaging patients) and barriers to implementation (including access to technology, responsibility, workflow, and the source of the app itself). Conclusion Our results show openness among oncology providers to using mHealth technology as part of patient care, but concerns regarding implementation. Designing acceptable apps may be challenging and require involvement of key stakeholders, partnering with trustworthy institutions, and outcome-based research.

scholarly journals Attitude of Health Care Providers on Snake Bite in Rural Community of Bangladesh

2018 ◽  
Vol 4 (1) ◽  
pp. 28-32
Author(s):  
Hafez Mohammad Nazmul Ahsan ◽  
Md Ridwanur Rahman ◽  
Robed Amin ◽  
Syed Mahbub Morshed ◽  
Md Amzad Hossain ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Rural Community ◽  
Service Providers ◽  
Target Population ◽  
Snake Bite ◽  
Survey Study ◽  
Effective Management ◽  
Care Providers ◽  
Attitude And Practice

Background: Health care providers have different attitude and practice about the snake bite in rural community of Bangladesh.Objective: The purpose of the present study was to know the attitude and practice about the snake bite in rural community of Bangladesh.Methodolgoy: The findings from survey study on snake bite have been elicited from face to face interview with 243 number of medical professionals/health service providers consisting of 113 number of MBBS doctors, 86 number of nurses and 46 number of other health practitioners. The study area consisted of 5 zillasadar hospitals and 15 upazilla health complexes. This study aims to assess the Attitude and Practice of snakebite in rural community and effective management of snake bite through community engagement and using health care system of Bangladesh approach for prevention of snakebite in rural community and effective management of snake bite for the rural Bangladeshi people. It uses the methodological triangulation qualitative and quantitative approach as well as a case study design in analyzing data, whereby the exploratory-descriptive design is followed.Result: We purposively select the 243 sample (Doctors, Nurses, Paramedics ,Others) from the selected districts and its consisting random upazillas from the govt. sector hospitals keeping in mind gender balance (Male-Female) as a primary total target population. So in total, 5 division and its consisting random upazilas hospital including union health complex hospital personnel (From District, Upazilla& Community Hospitals)will be interviewed throughout mention areas of Bangladesh. The findings show that 60.1% of doctors, 50.0% of nurses and 56.8% of practitioners have a notion that the snake bite victims would go to Ozha followed by 11.5% of doctors, 4.7% of nurses and 11.4% of practitioners have a notion that they would go to the local healers and that of 26.5% of doctors, 41.9% of nurses and 32.9% of practitioners mentioned that the snake bite victims would go to doctors. The findings show that 69.0% of doctors, 64.0% of nurses and 56.8% of practitioners will recommend not to apply ‘ tight bandage’ to victim’s snake bite spot and 67.3% of doctors, 65.1% of nurses and 13.6% of practitioners will recommend not to apply ‘Suction by mouth or chick’ to victim’s snake bite spot. The findings show that 82.3% of doctors, 90.7% of nurses and 70.5% of practitioners applied first aid to the snake bite victim as their common practice.Conclusion: Majority of health professionals are well informed regarding harmful traditions and measuresJournal of National Institute of Neurosciences Bangladesh, 2018;4(1): 28-32

scholarly journals Inconsistency of Timeliness in a Chief Complaint-Based Syndromic Surveillance System During Two Influenza Epidemic Seasons

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Tao Tao ◽  
Qi Zhao ◽  
Jun Zong ◽  
Xue Li ◽  
Vinod Diwan ◽  
...  
Keyword(s):  
Surveillance System ◽  
Syndromic Surveillance ◽  
Clinical Manifestations ◽  
Chief Complaint ◽  
Influenza Surveillance ◽  
Influenza Epidemic ◽  
Surveillance Network ◽  
Syndromic Surveillance System ◽  
Positive Rate ◽  
Patient Groups

This study estimated the early warning timeliness of a chief complaint-based syndromic surveillance system towards seasonal influenza epidemics. Findings showed that the timliness of ILI data sources changed across two influenza epidemic seasons. ILI reported from different levels of health facilities and patient groups showed distinct timeliness towards influenza epidemics indicated by virus positive rate (VPR) from National Influenza Surveillance Network. The changes of dominant strains, clinical manifestations, population groups affected in different influenza seasons might account for this inconsistency.

scholarly journals The Current Landscape of Pre-exposure Prophylaxis (PrEP) Service Delivery Models for Hiv Prevention: A Scoping Review

2020 ◽  
Author(s):  
Jef Vanhamel ◽  
Anke Rotsaert ◽  
Thijs Reyniers ◽  
Christiana Nöstlinger ◽  
Marie Laga ◽  
...  
Keyword(s):  
Hiv Prevention ◽  
Service Delivery ◽  
Health Care Providers ◽  
Scoping Review ◽  
Grey Literature ◽  
Target Population ◽  
Care Providers ◽  
Combination Prevention ◽  
Service Delivery Models ◽  
Delivery Models

Abstract Background: Strengthening HIV combination prevention is imperative given the continued high HIV incidence worldwide. The introduction of oral PrEP as a new biomedical HIV prevention tool can be a potential gamechanger because of its high clinical efficacy and the feasibility of making it available for different key populations.Experiences with different PrEP delivery models in a variety of settings and HIV epidemics will inform howits uptake and usage can be maximised.Methods: We conducted a scoping review using the five-step framework for conducting scoping studies provided by Arksey and O’Malley. We systematically searched the existing peer-reviewed international and grey literature describing four components of a PrEP service delivery model in real-world: the target population of PrEP services, the setting where PrEP was delivered, PrEP providers’ professionalisation and PrEP delivery channels. We restricted our search to English language articles. No geographical or time restrictions were set.Results: Following exclusion of ineligible records and removal of duplicates, 33 articles were retained for charting and analysing of the results. The target population of PrEP services was often described in terms of PrEP eligibility without targeting specific subgroups. If a specific target group was mentioned, PrEP was mainly offered to men who have sex with men (MSM). PrEP was often delivered centralisedin specialist clinics providing HIV, sexual health or STI care. Yet examples of de-centralised and community-based PrEP delivery have been reported. Health care providers delivering PrEP were mainly medical professionals, with task-shifting to non-traditional health professionals and lay providers identified in a minority of the studies. PrEP was mainly delivered through classic in-person visits. More innovative options using mHealth and telemedicine approaches to deliver specific parts of PrEP services are currently being applied.Conclusions: Within our scope for PrEP service delivery models, a range of possibilities was found for all components of such models. This reflects differentiation of care according to different contextual settings. More research is needed on how integration of services in these contexts could respond to the needs of different profiles of PrEPuserswithin a combination prevention approach.

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