The invasive stink bug Halyomorpha halys has become an important pest of many crops, causing severe economic losses to farmers. Control of the pest mainly relies on multiple applications of broad-spectrum insecticides, undermining the integrated pest management programs and causing secondary pest outbreaks. In the native area, egg parasitoids are the main natural enemies of H. halys, among which Trissolcus japonicus is considered the predominant species. In Italy, adventive populations of T. japonicus and Trissolcus mitsukurii, another egg parasitoid of H. halys in Japan, have established themselves. These two species, together with the indigenous Anastatus bifasciatus, are capable of attacking the eggs of the exotic host. Focusing on the situation in Northern Italy, where also the hyperparasitoid Acroclisoides sinicus is present, a discrete-time model is developed for the simulation of the pest evolution. It is based on actual field data collected over a timespan of five years. The simulations indicate that egg parasitoid by themselves do not suppress populations to non-pest levels, but can play an important role in reducing their impact. Both the data from the five-year surveys and those available in the literature are used in the model. It has some limitations in the fact that climatic conditions were not considered, while more accurate simulations could be performed with additional collection of field data, which at the moment are based on partial field observations not sampled at the same sites.
Citation: Ezio Venturino, Francesco Cantaloni, Luciana Tavella, Silvia Moraglio, Francesco Tortorici. Mathematical modeling of the parasitism and hyperparasitism increase on Halyomorpha halys eggs in a five-year survey in Northern Italy[J]. Mathematical Biosciences and Engineering, 2024, 21(11): 7501-7529. doi: 10.3934/mbe.2024330
| [1] | Brandy Rapatski, Petra Klepac, Stephen Dueck, Maoxing Liu, Leda Ivic Weiss . Mathematical epidemiology of HIV/AIDS in cuba during the period 1986-2000. Mathematical Biosciences and Engineering, 2006, 3(3): 545-556. doi: 10.3934/mbe.2006.3.545 |
| [2] | Peter Hinow, Pierre Magal, Shigui Ruan . Preface. Mathematical Biosciences and Engineering, 2015, 12(4): i-iv. doi: 10.3934/mbe.2015.12.4i |
| [3] | Khalid Hattaf, Noura Yousfi . Dynamics of SARS-CoV-2 infection model with two modes of transmission and immune response. Mathematical Biosciences and Engineering, 2020, 17(5): 5326-5340. doi: 10.3934/mbe.2020288 |
| [4] | Ayako Suzuki, Hiroshi Nishiura . Transmission dynamics of varicella before, during and after the COVID-19 pandemic in Japan: a modelling study. Mathematical Biosciences and Engineering, 2022, 19(6): 5998-6012. doi: 10.3934/mbe.2022280 |
| [5] | Deepalakshmi Sarkarai, Kalyani Desikan . QSPR/QSAR analysis of some eccentricity based topological descriptors of antiviral drugs used in COVID-19 treatment via Dε- polynomials. Mathematical Biosciences and Engineering, 2023, 20(9): 17272-17295. doi: 10.3934/mbe.2023769 |
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| [9] | Guest Editors: Azmy S. Ackleh, Rinaldo M. Colombo, Paola Goatin, Sander Hille, Adrian Muntean . Special issue: Mathematical Modeling with Measures. Mathematical Biosciences and Engineering, 2020, 17(3): 2451-2452. doi: 10.3934/mbe.2020133 |
| [10] | Gilberto González-Parra, Cristina-Luisovna Pérez, Marcos Llamazares, Rafael-J. Villanueva, Jesus Villegas-Villanueva . Challenges in the mathematical modeling of the spatial diffusion of SARS-CoV-2 in Chile. Mathematical Biosciences and Engineering, 2025, 22(7): 1680-1721. doi: 10.3934/mbe.2025062 |
The invasive stink bug Halyomorpha halys has become an important pest of many crops, causing severe economic losses to farmers. Control of the pest mainly relies on multiple applications of broad-spectrum insecticides, undermining the integrated pest management programs and causing secondary pest outbreaks. In the native area, egg parasitoids are the main natural enemies of H. halys, among which Trissolcus japonicus is considered the predominant species. In Italy, adventive populations of T. japonicus and Trissolcus mitsukurii, another egg parasitoid of H. halys in Japan, have established themselves. These two species, together with the indigenous Anastatus bifasciatus, are capable of attacking the eggs of the exotic host. Focusing on the situation in Northern Italy, where also the hyperparasitoid Acroclisoides sinicus is present, a discrete-time model is developed for the simulation of the pest evolution. It is based on actual field data collected over a timespan of five years. The simulations indicate that egg parasitoid by themselves do not suppress populations to non-pest levels, but can play an important role in reducing their impact. Both the data from the five-year surveys and those available in the literature are used in the model. It has some limitations in the fact that climatic conditions were not considered, while more accurate simulations could be performed with additional collection of field data, which at the moment are based on partial field observations not sampled at the same sites.
The special issue webpage is avaiable at: https://aimspress.com/mbe/article/5630/special-articles.
An outbreak of atypical pneumonia caused by a novel coronavirus was first identified in Wuhan, China in December 2019. The causative agent was initially called 2019 novel coronavirus (2019-nCoV), later renamed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the formal name for the associated disease given by the World Health Organization (WHO) is Coronavirus Disease 2019 (COVID-19). The virus swiftly spread to all areas of China and other countries. The WHO declared the coronavirus outbreak a public health emergency of international concern (PHEIC) on January 30, 2020. Mathematical models play an increasingly important role in forecasting transmission potential, optimizing control strategies, understanding the progression of infections within hosts, managing vaccine distribution and so on. These contributions have been recognized by many public health agencies like the WHO and the U.S. CDC.
To serve the needs of the fight against the COVID-19 pandemic, it is critical to accelerate the publication of modeling studies on COVID-19. With the support of Mathematical Biosciences and Engineering (MBE), we initiated a special issue entitled "Modeling the Biological, Epidemiological, Immunological, Molecular, Virological Aspects of COVID-19" on January 31, 2020. By the deadline of September 1, 2020, a total of 118 formal submissions from researchers across 40 countries around the world had been received, among which 38 papers were finally accepted for publication after peer review. Among the accepted contributions, the average times from submission to acceptance, and from acceptance to publication are 43 days and 9 days, respectively. The special issue covers a wide range of topics using different modeling approaches and different data sources.
The works of Zhou et al. (doi: 10.3934/mbe.2020147), Yang and Wang (10.3934/mbe.2020148), Chang et al. (10.3934/mbe.2020178), Feng et al. (10.3934/mbe.2020204), Aldila et al. (10.3934/mbe.2020335), Wang (10.3934/mbe.2020380), and Johnston and Pell (10.3934/mbe.2020401) investigate the role of behavior change or social distancing driven by media coverage or governmental action in curtailing the spread of COVID-19. The information propagation about COVID-19 in Chinese social media during the early phase of the epidemic is modeled and analyzed by Yin et al. (10.3934/mbe.2020146). Some studies focus on evaluating the impact of non-pharmaceutical interventions such as quarantine, isolation, personal hygiene, travel restriction and city lockdown on curbing the disease spread (Dai et al., 10.3934/mbe.2020152; Tian et al., 10.3934/mbe.2020158; Saldaña et al., 10.3934/mbe.2020231; Bugalia et al., 10.3934/mbe.2020318; Yousif and Ali, 10.3934/mbe.2020412; Srivastav et al., 10.3934/mbe.2021010). Some concentrate on assessing the importance of the timing to relax or lift mobility restrictions (Santana-Cibrian et al., 10.3934/mbe.2020330; Iboi et al., 10.3934/mbe.2020369). Some authors estimate key epidemiological parameters including basic reproduction number and effective reproduction number, peak time and peak size, final size, serial interval (Liu et al., 10.3934/mbe.2020172; Wang et al., 10.3934/mbe.2020173; Zhao, 10.3934/mbe.2020198; Feng et al., 10.3934/mbe.2020205). Besides human-to-human transmission, Yang and Wang (10.3934/mbe.2020148), Rong et al. (10.3934/mbe.2020149), Saldaña et al. (10.3934/mbe.2020231), and Zhong and Wang (10.3934/mbe.2020357) also take environment-to-human transmission into consideration. Some address the effect of delay in diagnosis (Rong et al., 10.3934/mbe.2020149), lack of medical resources (Wang et al., 10.3934/mbe.2020165), difference in interventions (Xia et al., 10.3934/mbe.2020274), incoming travelers (Deeb and Jalloul, 10.3934/mbe.2020302), superspreading events (Santana-Cibrian et al., 10.3934/mbe.2020330), nosocomial infections (Martos et al., 10.3934/mbe.2020410), transient behavior after mass vaccination (Akhavan Kharazian and Magpantay, 10.3934/mbe.2021019). Two models are proposed to describe SARS-CoV-2 dynamics in infected hosts (Li et al., 10.3934/mbe.2020159; Hattaf and Yousfi, 10.3934/mbe.2020288).
Most studies are based on deterministic ordinary differential equation type models whereas partial differential equation models (Zhu and Zhu, 10.3934/mbe.2020174; Wang and Yamamoto, 10.3934/mbe.2020266), complex network model (Yang et al., 10.3934/mbe.2020248), stochastic models (He et al., 10.3934/mbe.2020153; Olabode et al., 10.3934/mbe.2021050), discrete models (He et al., 10.3934/mbe.2020153, Li et al., 10.3934/mbe.2020208), individual-based model (Martos et al., 10.3934/mbe.2020410), and statistical models (Zhao, 10.3934/mbe.2020198; Nie et al., 10.3934/mbe.2020265; Xia et al., 10.3934/mbe.2020274; Chowdhury et al., 10.3934/mbe.2020323) are developed and analyzed as well. Early studies mainly deal with COVID-19 case data from China, and later studies fit models to data from various countries and regions including the United Kingdom (Feng et al., 10.3934/mbe.2020204), South Korea (Feng et al., 10.3934/mbe.2020205; Xia et al., 10.3934/mbe.2020274), Mexico (Saldaña et al., 10.3934/mbe.2020231; Santana-Cibrian et al., 10.3934/mbe.2020330), the United States (Wang and Yamamoto, 10.3934/mbe.2020266), Lebanon (Deeb and Jalloul, 10.3934/mbe.2020302), India (Bugalia et al., 10.3934/mbe.2020318; Srivastav et al., 10.3934/mbe.2021010), Indonesia (Aldila et al., 10.3934/mbe.2020335), Nigeria (Iboi et al., 10.3934/mbe.2020369), Canada (Wang, 10.3934/mbe.2020380), Saudi Arabia (Yousif and Ali, 10.3934/mbe.2020412) and so on. Mobile terminal positioning data (Nie et al., 10.3934/mbe.2020265) and Google community mobility data (Wang and Yamamoto, 10.3934/mbe.2020266) have also been used. In addition, Costris-Vas et al. (10.3934/mbe.2020383) write a survey paper on evaluating the accuracy of various models from recent pandemics.
With the broad spectrum of topics, we believe that these 38 peer-reviewed papers could represent a significant contribution of mathematical modeling in the fight against COVID-19. In fact, they have already received considerable attention in the field. For example, the paper by Yang and Wang (10.3934/mbe.2020148) is ranked the first most read paper in MBE with 2765 article views, 4465 PDF downloads and 54 citations. We hope the readers of this special issue will find helpful information for their own research and decision-making. So far, the ongoing COVID-19 pandemic has resulted in more than 85.62 million cases including 1.85 million deaths (data source: https://coronavirus.jhu.edu/map.html). With the joint efforts of health-care workers, vaccine developers, epidemiologists, modelers, the public and others, we look forward to returning to normal life in the near future.
The guest editors sincerely appreciate all authors for their valuable contributions and all referees for their constructive feedback. The guest editors thank the Editor-in-Chief, Professor Yang Kuang, and Editor-in-Chief of Mathematics section, Professor Shigui Ruan, for their kind invitation, and the Editorial Assistants for their patience and help, and the publisher AIMS for the generous support. Finally, DG acknowledge the financial support from the NSF of China (12071300), and NSF of Shanghai (20ZR1440600 and 20JC1413800). DH was partially supported by an Alibaba (China) Co. Ltd. Collaborative Research grant.
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Figures(7) / Tables(13)
Ezio Venturino, Francesco Cantaloni, Luciana Tavella, Silvia Moraglio, Francesco Tortorici. Mathematical modeling of the parasitism and hyperparasitism increase on Halyomorpha halys eggs in a five-year survey in Northern Italy[J]. Mathematical Biosciences and Engineering, 2024, 21(11): 7501-7529. doi: 10.3934/mbe.2024330
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