With the growing concern about the spread of new respiratory infectious diseases, several studies involving the application of technology in the prevention of these diseases have been carried out. Among these studies, it is worth highlighting the importance of those focused on the primary forms of prevention, such as social distancing, mask usage, quarantine, among others. This importance arises because, from the emergence of a new disease to the production of immunizers, preventive actions must be taken to reduce contamination and fatalities rates.
From the emergence of new infectious diseases, new research studies are also being carried out in order to contribute to their treatment motivated not only because of health crisis, but also social and economic impacts. However, until new medications or vaccines are produced, preventive measures are recommended by health organizations in order to reduce transmission among the population, such as social distancing, mask usage, isolation and quarantine [1][2][3][8,9,10].
Being a topic of considerable importance, especially due to the social, health and economic impacts to society, studies focused on the application of technology in the primary forms of prevention of new infectious diseases have attracted much attention and concern from institutions and researchers.
The scope of this SLR was to identify relevant studies that adopt information technology solutions in the primary ways of preventing respiratory infectious diseases transmission/spread.
From the findings, it was possible to identify six application domain categories in which there was a greater trend in studies related to pandemic planning and, among the support mechanisms adopted, data and mathematical application-related solutions received greater attention.
ID | Quality Assessment Question | Yes | Partially | No |
---|---|---|---|---|
Category | Studies | |||
Q1 | Are the study objectives and goals clearly specified? | 218 | ||
CD1: Healthcare and Clinical management (59) | (99.5%) |
1 (0.5%) |
S4, S11, S14, S21, S24, S25, S27, S31, S37, S38, S39, S40, S56, S57, S58, S59, S60, S61, S64, S70, S77, S80, S88, S89, S92, S93, S95, S103, S104, S112, S123, S126, S127, S133, S137, S139, S140, S141, S150, S151, S157, S158, S160, S168, S171, S181, S182, S183, S187, S191, S192, S197, S202, S203, S205, S206, S207, S218, S2190 (0.0%) |
|
Q2 | Is the study context clearly defined? | 113 (51.6%) |
Level | Classification | Description | ||||
---|---|---|---|---|---|---|
0 | No evidence | No evidence was presented regarding evaluation or validation | 89 (40.6%) |
17 (7.8%) |
||
CD2: Infection Testing/Screening (14) | S26, S35, S65, S82, S118, S122, S128, S148, S159, S163, S177, S185, S193, S198 | Q3 | Does the research design support the objectives/goals of the study? | 135 (61.6%) |
71 (32.4%) |
13 (5.9%) |
CD3: Mask Detection (16) | ||||||
1 | Example or demonstration | S6, S8, S47, S63, S74, S75, S76, S106, S107, S108, S121, S142, S143, S144, S152, S178 | Q4 | Does the study have an adequate description of the analysis of the data? | 96 (43.8%) |
67 (30.6%) |
Application description is provided with an example to aid its description | CD4: Pandemic Planning | 56 (25.6%) |
||||
(75) | S1, S2, S3, S5, S7, S15, S17, S23, S28, S29, S32, S36, S41, S43, S44, S45, S46, S48, S51, S53, S54, S55, S62, S66, S68, S71, S78, S81, S83, S85, S91, S96, S97, S98, S99, S100, S101, S102, S105, S111, S113, S116, S117, S120, S124, S125, S129, S130, S132, S138, S145, S146, S147, S153, S155, S156, S161, S164, S165, S169, S170, S173, S180, S186, S188, S189, S190, S199, S200, S201, S204, S209, S211, S215, S216 | Q5 | Does the study present a clear statement of the findings and provide enough data to support them? | 79 (36.1%) |
81 (37.0%) |
59 (26.9%) |
2 | CD5: Quarantine/isolation/containment/social distancing (24) | S10, S16, S19, S22, S30, S50, S52, S69, S79, S84, S90, S109, S110, S119, S131, S135, S167, S172, S174, S179, S184, S194, S195, S213 | Q6 | Do researchers critically examine potential bias and/or influence in the study? | 3 | |
CD6: Tracking, surveillance, and Contact tracing (31) | S9, S12, S13, S18, S20, S33, S34, S42, S49, S67, S72, S73, S86, S87, S94, S114, S115, S134, S136, S149, S154, S162, S166, S175, S176, S196, S208, S210, S212, S214, S217 |
(1.4%) |
33 | ||||
(15.1%) | ||||
183 | ||||
(83.6%) | ||||
Q7 | Study limitations are discussed explicitly? | 51 (23.3%) |
66 (30.1%) |
102 (46.6%) |
Category | Sub-Category | Support Mechanism | Studies |
---|---|---|---|
CS1: Data and Mathematical Application Related Solutions | Algorithms, Theories, Mathematical/Statistical Models | Bootstrap Method (1) | S170 |
Dijkstra Algorithm (1) | S16 | ||
Discrete Fourier Transform (DFT) model (1) | S65 | ||
Specialists Notes | Qualitative or textual assessments are provided. Example: advantages and disadvantages contrasts/comparation | General Algorithms, mathematical models/equations (12) | S9, S34, S49, S52, S69, S94, S102, S130, S156, S162, S210, S214 |
K-nearest Neighbor Algorithm, Nearest-neighbour distance (2) | S13, S167 | ||
Markov Model, Spatial Temporal Method, Graph Theory, NHPP, Monte Carlo (19) | |||
3 | Experiment in laboratory | S17, S18, S23, S34, S36, S44, S51, S53, S62, S85, S99, S101, S111, S116, S129, S149, S154, S215, S216 | |
Multi-agent (Model/simulation), Equation-based model (13) | S2, S3, S4, S5, S7, S91, S96, S99, S100, S125, S132, S160, S211 | ||
Multiple Signal Classification (MUSIC) Algorithm (1) | S128 | ||
Optimal Control Theory (1) | S161 | ||
Regression models, Short-term Prediction, RMSE, MAE (5) | S15, S68, S128, S147, S169 | ||
SEIR model, Grey Prediction Model, DSGE Algorithm, SLIR, SIS, SIR (24) | S21, S32, S55, S66, S91, S96, S97, S98, S116, S117, S129, S130, S145, S146, S153, S155, S161, S189, S190, S199, S200, S201, S209, S215 | ||
Self-Propelled Entity Dynamics (SPED) model, LDS—Low Discrepancy Sequence (1) | S164 | ||
Results are reached from simulations with artificial data in real experiments. Evidence collection is performed formally or informally. | |||
4 | Empirical Investigation | Real context investigation of the behavior of the proposed approach | |
5 | Artificial intelligence, Deep learning, Machine Learning, Big Data and Data mining | Big Data (5) | S1, S42, S81, S123, S147 |
Strict analysis | Evaluation/validation of the study is performed using a formal methodology. Example: questions and variables definition for analysis after the application of the approach | Decision Tree, Regression Tree, CART (5) | S40, S41, S46, S123, S180 |
DBSCAN—Density-Based Spatial Clustering of Applications with Noise (1) | S172 | ||
Fuzzy Logic (3) | S125, S171, S192 | ||
Heterogeneous Diffusion Network (1) | S154 | ||
K-means (5) | S33, S44, S180, S214, S217 | ||
LLA—Lexical Link Analysis (1) | S138 | ||
Logistic Regression (10) | S27, S45, S46, S55, S104, S149, S154, S169, S170, S177 | ||
Maximum Entropy Model (1) | S105 | ||
Naive Bayes (2) | S27, S41 | ||
NLP—Natural Language Processing (3) | S103, S137, S158 | ||
Neural network (CNN, MTCNN, MobileNet, others), Feature Enhancement Module (FEM), Spatial Separable Convolution, SSD (41) | S6, S8, S10, S20, S40, S41, S45, S47, S48, S55, S57, S58, S59, S60, S61, S63, S64, S65, S70, S74, S75, S76, S88, S90, S106, S107, S108, S109, S112, S120, S121, S142, S143, S144, S152, S178, S182, S184, S185, S201, S206 | ||
Random Forest, iForest (5) | S27, S33, S40, S41, S46 | ||
Support Vector Machine (8) | S3, S27, S40, S41, S45, S46, S61, S104 | ||
Vector Space Model (2) | S123, S141 | ||
CS2: Software/Systems/Apps/Programing languages | Market Software/Platform (Proprietary or Free/Open Source) | Android Studio (1) | S71, S135 |
AnyLogic, Django Framework (1) | S2 | ||
ArcGIS (3) | S28, S62, S208 | ||
Autodesk Revit/Meshmixer, Rhino3D, AutoCAD, Grasshopper (4) | S83, S110, S188, S199 | ||
Diseases | Studies | ||
---|---|---|---|
Infectious diseases in general (using or not some disease as examples) (62) |
S1, S3, S4, S5, S13, S21, S23, S28, S29, S36, S37, S42, S49, S53, S76, S85, S96, S101, S103, S105, S111, S113, S117, S118, S122, S123, S124, S126, S128, S129, S130, S132, S133, S146, S147, S149, S150, S151, S154, S156, S159, S160, S161, S162, S164, S165, S168, S172, S173, S177, S181, S182, S186, S187, S196, S197, S204, S208, S211, S213, S215, S219 | ||
AWS—Amazon Web | |||
COVID-19 | |||
Services (e.g., software, and load Balancer, elastic container, lambda, Greengrass, others) (3) | |||
S12, S62, S137 | |||
(139) |
S6, S8, S9, S10, S11, S12, S14, S15, S16, S18, S19, S20, S22, S24, S25, S26, S27, S30, S31, S32, S33, S34, S35, S38, S39, S40, S41, S43, S44, S45, S46, S47, S50, S52, S54, S55, S56, S57, S58, S59, S60, S61, S62, S63, S64, S65, S66, S67, S68, S69, S70, S71, S72, S73, S74, S75, S77, S78, S79, S80, S81, S82, S83, S84, S86, 87, S88, S89, S90, S92, S93, S94, S97, S98, S104, S106, S107, S108, S109, S110, S112, S119, S120, S121, S127, S131, S134, S135, S136, S137, S138, S139, S140, S141, S142, S143, S144, S145, S148, S152, S153, S157, S158, S163, S166, S167, S169, S170, S171, S174, S175, S176, S178, S179, S180, S183, S184, S185, S188, S189, S191, S192, S193, S194, S195, S198, S199, S200, S202, S203, S205, S206, S207, S209, S210, S214, 216, S217, S218 | ||
Bootstrap, Adobe Photoshop (1) | |||
S204 | |||
Influenza (H1N1, H5N1, and others) (17) |
|||
Business Model Canvas (BMC), Service Blueprint (1) | |||
S124 | |||
Ethereum (1) | |||
S67 | |||
S2, S7, S17, S48, S51, S91, S99, S100, S102, S114, S115, S116, S125, S155, S190, S201, S212 | |||
Klebsiella pneumoniae (1) | S195 | Google Cloud Platform (2) | S62, S68 |
Hadoop (1) | S42 | ||
Hyperledger Fabric (1) | S117 | ||
IOTA Tangle Platform (1) | S71 | ||
Kibana (Elasticsearch) (1) | S62 | ||
MATLAB (1) | S113 | ||
Microsoft Azure Cloud (2) | S70, S78 | ||
NetLogo (1) | S4 | ||
NLTK—Natural Language Toolkit (1) | S158 | ||
Node.js (2) | S62, S137 | ||
Node-RED and Grafana (1) | S136 | ||
OpenCV (2) | S109, S151 | ||
Ultimaker Cura (1) | S110 | ||
Unity Platform (e.g., WebGL, 3D) (3) | S83, S131, S179 | ||
WeChat, WhatsApp, WhatsApp Bot (4) | S93, S109, S111, S117 | ||
Wireshark Dumpcap (1) | S195 | ||
Zoom Platform (1) | S207 | ||
Mobile, Desktop, WEB or Cloud Application/Framework proposed as study contributions | Cloud Application (3) | S12, S31, S35 | |
Desktop Application (4) | S51, S83, S96, S113 | ||
Mobile Application (24) | S12, S20, S33, S63, S70, S72, S73, S84, S92, S111, S115, S119, S123, S135, S150, S151, S165, S166, S175, S192, S194, S203, S204, S214 | ||
Web Application/Framework (21) | S2, S14, S28, S29, S37, S41, S42, S62, S67, S68, S78, S82, S93, S123, S131, S158, S165, S166, S176, S204, S214 | ||
Programming Languages | C#, C++ (2) | S83, S96 | |
Java (J2EE, J2ME, JNI, Hibernate) (5) | S14, S28, S37, S73, S92 | ||
JavaScript Libraries/ API (e.g., jQuery, ReactJS, AJAX, Google Web Toolkits, Google Maps) (9) | S2, S67, S28, S29, S72, S151, S166, S196, S204 | ||
PHP (2) | S166, S204 | ||
Python (6) | S2, S83, S96, S158, S199, S216 | ||
Visual Basic (1) | S51 | ||
Data Base Management System | Firebase (4) | S71, S73, S92, S194 | |
Influx DB (1) | S136 | ||
MongoDB (2) | S2, S42 | ||
MYSQL (3) | S78, S123, S204 | ||
MS Access (1) | S51 | ||
Oracle (1) | S29 | ||
PostgreSQL (2) | S37, S208 | ||
Neo4j (1) | S12 | ||
SQLite (1) | S83 | ||
CS3: Internet of Things and Hardware | *1 | Wearable devices (e.g.,smartwatches, smartphones, smartbelt, and others) (17) | S19, S27, S40, S54, S56, S69, S70, S79, S111, S115, S139, S157, S163, S175, S181, S195, S213 |
Sensors (mobile or fixed), Cameras, RFID (Radio Frequency Identification) |
Cameras—photo and video (Fixed and mobile) (11) |
S30, S74, S82, S106, S109, S118, S121, S122, S128, S193, S194 | |
Environment Sensors (e.g., Passive Infrared (PIR) Sensor, and others) (26) | S11, S16, S21, S30, S38, S47, S50, S54, S74, S77, S82, S89, S109, S114, S121, S122, S126, S127, S135, S136, S172, S177, S185, S191, S192, S193 | ||
RFID (Radio Frequency Identification) devices (9) | S13, S27, S30, S35, S50, S182, S185, S192, S196 | ||
Wearable and/or mobile body sensors (e.g., temperature, cough, oxygen, pressure, heart rate measurement) (14) | S21, S25, S26, S27, S31, S35, S44, S69, S86, S87, S118, S157, S159, S181 | ||
Others (e.g., Printers, Spray, Chips, GPS/GSM/Bluetooth devices, WIFI routers, UV tech, WBAN, and others) | Bluetooth/WIFI/GPS/Wireless devices (e.g., module, routers, access point, receivers, SMS gateways, GPS chips, and others) (21) | S9, S18, S26, S31, S44, S50, S84, S86, S123, S124, S134, S136, S142, S148, S172, S175, S194, S196, S207, S212, S219 | |
Desktops, Laptops, and computer accessories (e.g., memory cards, processors, and other boards) (21) | S25, S31, S39, S47, S74, S86, S109, S114, S121, S123, S134, S136, S137, S139, S185, S191, S192, S197, S198, S207, S219 | ||
Printer and scan devices (3) | S110, S174, S218 | ||
Spray/Dispenser devices (6) | S11, S82, S168, S191, S205, S219 | ||
UV technology (e.g., UVC, UV Chip, UV Led, UV Light, UV ray) (7) | S11, S24, S38, S95, S127, S133, S148 | ||
Robot/Drones | Robot/Drones/Unmanned Aerial Vehicles (UAV) (14) | S18, S22, S43, S80, S90, S127, S140, S167, S173, S183, S187, S198, S205, S218 | |
CS4: Blockchain | *1 | Blockchain (7) | S43, S67, S71, S117, S162, S173, S186 |
Objective | Item | Objective | Item |
---|
Evidence Level | Context | |||||
---|---|---|---|---|---|---|
Academic (121) | Industrial (98) | |||||
General Data | Title | |||||
0: No evidence (13) |
S3, S11, S20, S25, S53, S56, S70, S124, S126, S141, S150, S177, S181,RQ5 | Context | ||||
* | 1 | Author(s) | Q1 | Objective of the Study | ||
1: Example or demonstration (36) |
S1, S5, S9, S12, S26, S30, S31, S33, S36, S50, S67, S69, S79, S81, S82, S84, S87, S101, S107, S127, S133, S134, S140, S146, S163, S165, S166, S175, S179, S185, S191, S193, S197, S208, S213, S214, | *1 | Publication Year | Q2 | Description of the Context | |
2: Specialists Notes (7) | S14, S47, S71, S72, S86, S174, S194, | Venue | Q3 | Description of the Research Project | ||
* | 1 | Paper Summary | Q4 | Analysis of the Data | ||
RQ1 | Approach | Q5 | Conclusions Presentation | |||
3: Experiment in laboratory (117) |
S2, S7, S8, S10, S13, S16, S18, S34, S40, S43, S44, S49, S51, S52, S54, S59, S62, S64, S66, S75, S80, S89, S90, S91, S94, S96, S98, S99, S100, S102, S103, S104, S105, S109, S112, S115, S119, S121, S122, S129, S132, S142, S145, S151, S153, S156, S158, S159, S161, S162, S164, S171, S172, S173, S180, S182, S186, S190, S200, S206, S209, S210, S211, S215, S219 | S4, S6, S17, S23, S37, S38, S39, S41, S60, S61, S65, S68, S74, S76, S77, S92, S95, S106, S108, S110, S111, S113, S116, S117, S118, S120, S123, S125, S128, S136, S138, S143, S147, S148, S152, S155, S160, S167, S170, S183, S184, S187, S188, S189, S195, S196, S198, S199, S202, S204, S216, S218 | ||||
4: Empirical Investigation (24) |
*1 | S19, S22, S27, S28, S29, S32, S46, S55, S73, S83, S85, S88, S93, S130, S131, S135, S139, S154, S169, S176, S203, S205, S207, S212, | ||||
5: Strict analysis (22) | *1 | S15, S21, S24, S35, S42, S45, S48, S57, S58, S63, S78, S97, S114, S137, S144, S149, S157, S168, S178, S192, S201, S217 | RQ2 | Application Domain | Q6 | Critical Analysis Description |
RQ3 | Adopted Support Mechanisms | Q7 | Description of Limitations and Bias | |||
RQ4 | Level of Evidence |