MOOD publications

@article{Mäkelä2025,

title = {Knowledge, attitudes, and practices towards vector-borne diseases in changing climate in Finland},

author = {Henna Mäkelä, Timothée Dub, J. Pekka Nuorti, Jussi Sane},

doi = {https://doi.org/10.1017/s0950268824001468},

year  = {2025},

date = {2025-01-15},

urldate = {2025-01-15},

journal = {Epidemiology and Infection},

abstract = {With climate change, the geographic distribution of some VBDs has expanded, highlighting the need for adaptation, and managing the risks associated with emergence in new areas. We conducted a questionnaire survey on the knowledge, attitudes, and practices (KAP) about vector-borne diseases (VBDs) among sample of Finnish residents. The questions were scored and the level of KAP was determined based on scoring as poor, fair, good, or excellent. Binary logistic regression analysis was used to evaluate the associations of different KAP levels with sex, age, education, and possible previous VPD infection. },

keywords = {CHIK (Chikungunya), DEN (Dengue), Zika},

pubstate = {published},

tppubtype = {article}

}

@article{Re2024b,

title = {VectAbundance: a spatio-temporal database of vector observations},

author = {Daniele Da Re, Giovanni Marini, Carmelo Bonannella, Fabrizio Laurini, Mattia Manica, Nikoleta Anicic, Alessandro Albieri, Paola Angelini, Daniele Arnoldi, Marharyta Blaha, Federica Bertola, Beniamino Caputo, Claudio De Liberato, Alessandra Della Torre, Enkelejda Velo, Eleonora Flacio, Alessandra Franceschini, Francesco Gradoni, Përparim Kadriaj, Valeria Lencioni, Irene Del Lesto, Francesco La Russa, Riccardo Paolo Lia, Fabrizio Montarsi, Domenico Otranto, Gregory L’Ambert, Annapaola Rizzoli, Pasquale Rombolà, Federico Romiti, Gionata Stancher, Alessandra Torina, Chiara Virgillito, Fabiana Zandonai, Roberto Rosà},

doi = {https://doi.org/10.1038/s41597-024-03482-y},

year  = {2024},

date = {2024-06-15},

journal = {Scientific Data},

abstract = {Modelling approaches play a crucial role in supporting local public health agencies by estimating and forecasting vector abundance and seasonality. However, the reliability of these models is contingent on the availability of standardized, high-quality data. Addressing this need, our study focuses on collecting and harmonizing egg count observations of the mosquito Aedes albopictus, obtained through ovitraps in monitoring and surveillance efforts across Albania, France, Italy, and Switzerland from 2010 to 2022. We processed the raw observations to obtain a continuous time series of ovitraps observations allowing for an extensive geographical and temporal coverage of Ae. albopictus population dynamics. The resulting post-processed observations are stored in the open-access database VectAbundance.This initiative addresses the critical need for accessible, high-quality data, enhancing the reliability of modelling efforts and bolstering public health preparedness.



},

keywords = {CHIK (Chikungunya), DEN (Dengue), Zika},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Prior water availability modifies the effect of heavy rainfall on dengue transmission: a time series analysis of passive surveillance data from southern China},

author = {Qu Cheng and Qinlong Jing and Philip A. Collender and Jennifer R. Head and Qi Li and Hailan Yu and Zhichao Li and Yang Ju and Tianmu Chen and Peng Wang and Eimear Cleary and Shengjie Lai},

url = {https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1287678/full},

doi = {10.3389/fpubh.2023.1287678},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {Frontiers Public Health},

volume = {11},

abstract = {Introduction: Given the rapid geographic spread of dengue and the growing frequency and intensity of heavy rainfall events, it is imperative to understand the relationship between these phenomena in order to propose effective interventions. However, studies exploring the association between heavy rainfall and dengue infection risk have reached conflicting conclusions, potentially due to the neglect of prior water availability in mosquito breeding sites as an effect modifier.



Methods: In this study, we addressed this research gap by considering the impact of prior water availability for the first time. We measured prior water availability as the cumulative precipitation over the preceding 8 weeks and utilized a distributed lag non-linear model stratified by the level of prior water availability to examine the association between dengue infection risk and heavy rainfall in Guangzhou, a dengue transmission hotspot in southern China.



Results: Our findings suggest that the effects of heavy rainfall are likely to be modified by prior water availability. A 24–55 day lagged impact of heavy rainfall was associated with an increase in dengue risk when prior water availability was low, with the greatest incidence rate ratio (IRR) of 1.37 [95% credible interval (CI): 1.02–1.83] occurring at a lag of 27 days. In contrast, a heavy rainfall lag of 7–121 days decreased dengue risk when prior water availability was high, with the lowest IRR of 0.59 (95% CI: 0.43–0.79), occurring at a lag of 45 days.



Discussion: These findings may help to reconcile the inconsistent conclusions reached by previous studies and improve our understanding of the complex relationship between heavy rainfall and dengue infection risk.},

keywords = {DEN (Dengue), OpenDataSet},

pubstate = {published},

tppubtype = {article}

}