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Ebola and other emerging infectious diseases
Published in Saleem H. Ali, Kathryn Sturman, Nina Collins, Africa’s Mineral Fortune, 2018
Osman A. Dar, Francesca Viliani, Hisham Tariq, Emmeline Buckley, Abbas Omaar, Eloghene Otobo, David L. Heymann
A review of EIDs in the past 60 years suggests that over 60 percent of these diseases were transmitted from animals; of those animal-transmitted diseases, just over 70 percent came from wild animals and the rest from domesticated animals.5 An example of an EID is Zika fever, a mosquito-borne viral disease. Zika was first identified in a non-human primate in the Zika Forest of Uganda in 1947, and gradually moved east across the Pacific before appearing in Brazil in 2014. Since that year it has spread rapidly across communities in south and central America and the Caribbean. Zika is associated with microcephaly and Guillain-Barré syndrome, among other neurologic syndromes, and has had a detrimental effect on trade and commerce in the affected areas.6
Exploiting Arthropod Midgut Components for Development of Interventions against Infectious Diseases
Published in Hajiya Mairo Inuwa, Ifeoma Maureen Ezeonu, Charles Oluwaseun Adetunji, Emmanuel Olufemi Ekundayo, Abubakar Gidado, Abdulrazak B. Ibrahim, Benjamin Ewa Ubi, Medical Biotechnology, Biopharmaceutics, Forensic Science and Bioinformatics, 2022
Oluwafemi Abiodun Adepoju, Bashiru Ibrahim, Emmanuel Oluwadare Balogun
Mosquitoes are the most important vectors of infectious diseases in sub-Saharan Africa. They are hosts to diverse groups of microorganisms, including bacteria, fungi, and viruses (Gao et al., 2020). Aedes transmit viruses of Dengue fever, Chikungunya, Rift Valley fever, Yellow fever, Zika fever, and lymphatic filariasis parasite (WHO, 2020a). The Anopheles mosquito transmits the parasites causing malaria and lymphatic filariasis (WHO, 2020a). Plasmodium falciparum is responsible for the highest mortality due to malaria especially in children under 5 years and women getting pregnant for the first time (Nikolaeva et al., 2020).
Temporal trends of dengue cases and deaths from 2007 to 2020 in Belo Horizonte, Brazil
Published in International Journal of Environmental Health Research, 2023
Maria da Consolação Magalhães Cunha, Bianca Conrad Bohm, Maria Helena Franco Morais, Natalia Bruna Dias Campos, Olivia Lang Schultes, Nádia Pereira Campos Bruhn, Fabio Raphael Pascoti Bruhn, Waleska Teixeira Caiaffa
Dengue, the most prevalent arbovirus infection in the world, is an infectious, febrile, and acute disease, endemic in more than one hundred countries in Africa, the Americas, the Eastern Mediterranean, Southeast Asia, and the Western Pacific (WHO 2020). The vector, the Ae. aegypti mosquito, was probably introduced to Brazil during the colonial period (between the 16th and 19th centuries), with the maritime traffic from Africa. Considered as eradicated in the 1950s, it was reintroduced in the late 1960s (Oliveira 2015). The four types of dengue viruses in circulation (DENV-1, DENV-2, DENV-3,and DENV 4) are present in Brazil (Fares et al. 2015; OPAS/OMS/Brasil 2019). Currently, Ae. aegypti has its epidemiological importance expanded as it also transmits the viruses of yellow fever, Zika fever, and chikungunya (Gubler 2011; Fares et al. 2015; Valle et al. 2016; BRASIL 2017; OPAS/OMS/Brasil 2019).
Measures to prevent and control the spread of novel coronavirus disease (COVID-19) infection in tourism locations
Published in SICE Journal of Control, Measurement, and System Integration, 2022
Hideyuki Nagai, Setsuya Kurahashi
Agent-based models excel at the manifestation of effects through micro-level behavioural changes among individual citizens as specific intervention measures against infection, as well as at operability based on intervention scenario findings. Therefore, they are used with existing infectious diseases, such as smallpox [11–13], measles [14,15], Zika fever [16], Ebola haemorrhagic fever [16,17], and rubella [18]. As for the proposed COVID-19 simulations, most are based on macro-scale mathematical models including the studies discussed in the previous section, but there are also some interesting agent-based models. Ferguson et al. reported that non-medical intervention such as wider social distancing, home isolation, and home quarantine throughout the UK and the United States may mitigate the spread of the infection to some degree, but as long as there is no prevention system such as a vaccine or antiviral drug, pressure on medical resources is unavoidable, and large numbers of fatalities are likely [19]. Based on this report, the UK government shifted immediately from its initial mass immunization strategy to strict intervention measures to ensure social distancing. Silva et al. simulated not only the epidemiological dynamics but also an estimation of the economic effect of various intervention scenarios with regard to ensuring social distancing and demonstrated that where a lockdown is unfeasible because of the scale of economic impact, a combination of the use of face masks and partial isolation is more realistic [20]. Aleta et al. constructed an agent-based model based on census research and movement data in the greater Boston area and demonstrated that by means of testing, contact tracing, and home quarantine after a period of strict social distancing, it was possible to resume economic activity while protecting the health system [21].
A model comparison algorithm for increased forecast accuracy of dengue fever incidence in Singapore and the auxiliary role of total precipitation information
Published in International Journal of Environmental Health Research, 2018
Yew-Meng Koh, Reagan Spindler, Matthew Sandgren, Jiyi Jiang
A variety of potential predictor variables was considered. Among these were weekly Zika fever incidence counts, weekly maximum temperature, and weekly total rainfall. As mentioned in the ‘Introduction’ section, Zika fever is also an Aedes mosquito-borne illness. The correlation between once-differenced Zika incidence and once-differenced DF incidence was found to be weak. This relationship is displayed in Figure 2.