Background: Contact tracing (CT) is a primary means of controlling infectious diseases, such as coronavirus disease 2019 (COVID-19), especially in the early months of the pandemic. Objectives: This work is a systematic review of mathematical models used during the COVID-19 pandemic that explicitly parameterise CT as a potential mitigator of the effects of the pandemic. Methods: This review is registered in PROSPERO. A comprehensive literature search was conducted using the PubMed, EMBASE, Cochrane Library, CINAHL, and Scopus databases. Two reviewers independently selected the title/abstract, full text, data extraction, and risk of bias. Disagreements were resolved through discussion. The characteristics of the studies and mathematical models were collected from each study. Results: A total of 53 articles out of 2101 were included. The modelling of the COVID-19 pandemic was the main objective of 23 studies, while the remaining articles evaluated the forecast transmission of COVID-19. Mo...
Mathematical Contact Tracing Models for the COVID-19 Pandemic: A Systematic Review of the Literature
	
	
	
		
		
		
		
		
	
	
	
	
	
	
	
	
		
		
		
		
		
			
			
			
		
		
		
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
						
							
							
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
			
			
				
				
					
					
					
					
						
							
						
						
					
				
				
				
				
				
				
				
				
				
				
				
			
			
		
		
		
		
	
Ocagli H.;Brigiari G.;Mongillo M.;F. Gentili;Gregori, D
	
		
		
	
			2025
Abstract
Background: Contact tracing (CT) is a primary means of controlling infectious diseases, such as coronavirus disease 2019 (COVID-19), especially in the early months of the pandemic. Objectives: This work is a systematic review of mathematical models used during the COVID-19 pandemic that explicitly parameterise CT as a potential mitigator of the effects of the pandemic. Methods: This review is registered in PROSPERO. A comprehensive literature search was conducted using the PubMed, EMBASE, Cochrane Library, CINAHL, and Scopus databases. Two reviewers independently selected the title/abstract, full text, data extraction, and risk of bias. Disagreements were resolved through discussion. The characteristics of the studies and mathematical models were collected from each study. Results: A total of 53 articles out of 2101 were included. The modelling of the COVID-19 pandemic was the main objective of 23 studies, while the remaining articles evaluated the forecast transmission of COVID-19. Mo...| File | Dimensione | Formato | |
|---|---|---|---|
| healthcare-13-00935-v2.pdf accesso aperto 
											Tipologia:
											Published (Publisher's Version of Record)
										 
											Licenza:
											
											
												Creative commons
												
												
													
													
													
												
												
											
										 
										Dimensione
										1.23 MB
									 
										Formato
										Adobe PDF
									 | 1.23 MB | Adobe PDF | Visualizza/Apri | 
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.




