MOOD project is at the forefront of European research of infectious disease surveillance and modelling from a data science perspective, investigating the impact of global warming on disease outbreaks, and proposing innovations for building of One Health systems across Europe and the world.
In the table below all publications to which the MOOD project contributed are listed. Use the filter to select the most relevant articles.
Manica, Mattia; Marini, Giovanni; Solimini, Angelo; Guzzetta, Giorgio; Poletti, Piero; Scognamiglio, Paola; Virgillito, Chiara; della Torre, Alessandra; Merler, Stefano; Rosà, Roberto; Vairo, Francesco; Caputo, Beniamino
Reporting delays of chikungunya cases during the 2017 outbreak in Lazio region, Italy Journal Article
In: 2023.
Abstract | Links | BibTeX | Tags: CHIK (Chikungunya)
@article{nokey,
title = {Reporting delays of chikungunya cases during the 2017 outbreak in Lazio region, Italy},
author = {Mattia Manica and Giovanni Marini and Angelo Solimini and Giorgio Guzzetta and Piero Poletti and Paola Scognamiglio and Chiara Virgillito and Alessandra della Torre and Stefano Merler and Roberto Rosà and Francesco Vairo and Beniamino Caputo
},
url = {https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0011610},
doi = {10.1371/journal.pntd.0011610},
year = {2023},
date = {2023-09-14},
urldate = {2023-09-14},
abstract = {Background
Emerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission.
Methodology/principal findings
Using descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak.
Conclusions/significance
These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.},
keywords = {CHIK (Chikungunya)},
pubstate = {published},
tppubtype = {article}
}
Emerging arboviral diseases in Europe pose a challenge due to difficulties in detecting and diagnosing cases during the initial circulation of the pathogen. Early outbreak detection enables public health authorities to take effective actions to reduce disease transmission. Quantification of the reporting delays of cases is vital to plan and assess surveillance and control strategies. Here, we provide estimates of reporting delays during an emerging arboviral outbreak and indications on how delays may have impacted onward transmission.
Methodology/principal findings
Using descriptive statistics and Kaplan-Meyer curves we analyzed case reporting delays (the period between the date of symptom onset and the date of notification to the public health authorities) during the 2017 Italian chikungunya outbreak. We further investigated the effect of outbreak detection on reporting delays by means of a Cox proportional hazard model. We estimated that the overall median reporting delay was 15.5 days, but this was reduced to 8 days after the notification of the first case. Cases with symptom onset after outbreak detection had about a 3.5 times higher reporting rate, however only 3.6% were notified within 24h from symptom onset. Remarkably, we found that 45.9% of identified cases developed symptoms before the detection of the outbreak.
Conclusions/significance
These results suggest that efforts should be undertaken to improve the early detection and identification of arboviral cases, as well as the management of vector species to mitigate the impact of long reporting delays.
Guzzetta, Giorgio; Vairo, Francesco; Mammone, Alessia; Lanini, Simone; Poletti, Piero; Manica, Mattia; Rosa, Roberto; Caputo, Beniamino; Solimini, Angelo; Torre, Alessandra Della; others,
Spatial modes for transmission of chikungunya virus during a large chikungunya outbreak in Italy: a modeling analysis Journal Article
In: BMC medicine, vol. 18, no. 1, pp. 1–10, 2020.
Abstract | Links | BibTeX | Tags: CHIK (Chikungunya), OpenDataSet
@article{guzzetta2020spatial,
title = {Spatial modes for transmission of chikungunya virus during a large chikungunya outbreak in Italy: a modeling analysis},
author = {Giorgio Guzzetta and Francesco Vairo and Alessia Mammone and Simone Lanini and Piero Poletti and Mattia Manica and Roberto Rosa and Beniamino Caputo and Angelo Solimini and Alessandra Della Torre and others},
doi = {https://doi.org/10.1186/s12916-020-01674-y},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {BMC medicine},
volume = {18},
number = {1},
pages = {1--10},
publisher = {BioMed Central},
abstract = {Background
The spatial spread of many mosquito-borne diseases occurs by focal spread at the scale of a few hundred meters and over longer distances due to human mobility. The relative contributions of different spatial scales for transmission of chikungunya virus require definition to improve outbreak vector control recommendations.
Methods
We analyzed data from a large chikungunya outbreak mediated by the mosquito Aedes albopictus in the Lazio region, Italy, consisting of 414 reported human cases between June and November 2017. Using dates of symptom onset, geographic coordinates of residence, and information from epidemiological questionnaires, we reconstructed transmission chains related to that outbreak.
Results
Focal spread (within 1 km) accounted for 54.9% of all cases, 15.8% were transmitted at a local scale (1–15 km) and the remaining 29.3% were exported from the main areas of chikungunya circulation in Lazio to longer distances such as Rome and other geographical areas. Seventy percent of focal infections (corresponding to 38% of the total 414 cases) were transmitted within a distance of 200 m (the buffer distance adopted by the national guidelines for insecticide spraying). Two main epidemic clusters were identified, with a radius expanding at a rate of 300–600 m per month. The majority of exported cases resulted in either sporadic or no further transmission in the region.
Conclusions
Evidence suggest that human mobility contributes to seeding a relevant number of secondary cases and new foci of transmission over several kilometers. Reactive vector control based on current guidelines might allow a significant number of secondary clusters in untreated areas, especially if the outbreak is not detected early. Existing policies and guidelines for control during outbreaks should recommend the prioritization of preventive measures in neighboring territories with known mobility flows to the main areas of transmission.},
keywords = {CHIK (Chikungunya), OpenDataSet},
pubstate = {published},
tppubtype = {article}
}
The spatial spread of many mosquito-borne diseases occurs by focal spread at the scale of a few hundred meters and over longer distances due to human mobility. The relative contributions of different spatial scales for transmission of chikungunya virus require definition to improve outbreak vector control recommendations.
Methods
We analyzed data from a large chikungunya outbreak mediated by the mosquito Aedes albopictus in the Lazio region, Italy, consisting of 414 reported human cases between June and November 2017. Using dates of symptom onset, geographic coordinates of residence, and information from epidemiological questionnaires, we reconstructed transmission chains related to that outbreak.
Results
Focal spread (within 1 km) accounted for 54.9% of all cases, 15.8% were transmitted at a local scale (1–15 km) and the remaining 29.3% were exported from the main areas of chikungunya circulation in Lazio to longer distances such as Rome and other geographical areas. Seventy percent of focal infections (corresponding to 38% of the total 414 cases) were transmitted within a distance of 200 m (the buffer distance adopted by the national guidelines for insecticide spraying). Two main epidemic clusters were identified, with a radius expanding at a rate of 300–600 m per month. The majority of exported cases resulted in either sporadic or no further transmission in the region.
Conclusions
Evidence suggest that human mobility contributes to seeding a relevant number of secondary cases and new foci of transmission over several kilometers. Reactive vector control based on current guidelines might allow a significant number of secondary clusters in untreated areas, especially if the outbreak is not detected early. Existing policies and guidelines for control during outbreaks should recommend the prioritization of preventive measures in neighboring territories with known mobility flows to the main areas of transmission.