Mathematical assessment of control strategies against the spread of MERS-CoV in humans and camels in Saudi Arabia

Adel Alatawi; Abba B. Gumel; Adel Alatawi; Abba B. Gumel

doi:10.3934/mbe.2024281

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 7: 6425-6470. doi: 10.3934/mbe.2024281

Previous Article Next Article

Research article Special Issues

Mathematical assessment of control strategies against the spread of MERS-CoV in humans and camels in Saudi Arabia

Adel Alatawi ^1,2,
Abba B. Gumel ^{3,4
,
,}

1.
Department of Mathematics, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi Arabia
2.
Biodiversity Genomics Unit, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi Arabia
3.
Department of Mathematics, University of Maryland, College Park, MD, 20742, USA
4.
Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria 0002, South Africa

Academic Editor: Xueying Wang

Received: 28 January 2024 Revised: 04 June 2024 Accepted: 14 June 2024 Published: 01 July 2024

A new mathematical model for the transmission dynamics and control of the Middle Eastern respiratory syndrome (MERS), a respiratory virus caused by MERS-CoV coronavirus (and primarily spread to humans by dromedary camels) that first emerged out of the Kingdom of Saudi Arabia (KSA) in 2012, was designed and used to study the transmission dynamics of the disease in a human-camel population within the KSA. Rigorous analysis of the model, which was fitted and cross-validated using the observed MERS-CoV data for the KSA, showed that its disease-free equilibrium was locally asymptotically stable whenever its reproduction number (denoted by $ {\mathbb R}_{0M} $) was less than unity. Using the fixed and estimated parameters of the model, the value of $ {\mathbb R}_{0M} $ for the KSA was estimated to be 0.84, suggesting that the prospects for MERS-CoV elimination are highly promising. The model was extended to allow for the assessment of public health intervention strategies, notably the potential use of vaccines for both humans and camels and the use of face masks by humans in public or when in close proximity with camels. Simulations of the extended model showed that the use of the face mask by humans who come in close proximity with camels, as a sole public health intervention strategy, significantly reduced human-to-camel and camel-to-human transmission of the disease, and this reduction depends on the efficacy and coverage of the mask type used in the community. For instance, if surgical masks are prioritized, the disease can be eliminated in both the human and camel population if at least 45% of individuals who have close contact with camels wear them consistently. The simulations further showed that while vaccinating humans as a sole intervention strategy only had marginal impact in reducing the disease burden in the human population, an intervention strategy based on vaccinating camels only resulted in a significant reduction in the disease burden in camels (and, consequently, in humans as well). Thus, this study suggests that attention should be focused on effectively combating the disease in the camel population, rather than in the human population. Furthermore, the extended model was used to simulate a hybrid strategy, which combined vaccination of both humans and camels as well as the use of face masks by humans. This simulation showed a marked reduction of the disease burden in both humans and camels, with an increasing effectiveness level of this intervention, in comparison to the baseline scenario or any of the aforementioned sole vaccination scenarios. In summary, this study showed that the prospect of the elimination of MERS-CoV-2 in the Kingdom of Saudi Arabia is promising using pharmaceutical (vaccination) and nonpharmaceutical (mask) intervention strategies, implemented in isolation or (preferably) in combination, that are focused on reducing the disease burden in the camel population.
- MERS-CoV-2,
- dromedary camels,
- vaccination,
- face mask,
- reproduction number
Citation: Adel Alatawi, Abba B. Gumel. Mathematical assessment of control strategies against the spread of MERS-CoV in humans and camels in Saudi Arabia[J]. Mathematical Biosciences and Engineering, 2024, 21(7): 6425-6470. doi: 10.3934/mbe.2024281

Related Papers:

Abstract

A new mathematical model for the transmission dynamics and control of the Middle Eastern respiratory syndrome (MERS), a respiratory virus caused by MERS-CoV coronavirus (and primarily spread to humans by dromedary camels) that first emerged out of the Kingdom of Saudi Arabia (KSA) in 2012, was designed and used to study the transmission dynamics of the disease in a human-camel population within the KSA. Rigorous analysis of the model, which was fitted and cross-validated using the observed MERS-CoV data for the KSA, showed that its disease-free equilibrium was locally asymptotically stable whenever its reproduction number (denoted by $ {\mathbb R}_{0M} $) was less than unity. Using the fixed and estimated parameters of the model, the value of $ {\mathbb R}_{0M} $ for the KSA was estimated to be 0.84, suggesting that the prospects for MERS-CoV elimination are highly promising. The model was extended to allow for the assessment of public health intervention strategies, notably the potential use of vaccines for both humans and camels and the use of face masks by humans in public or when in close proximity with camels. Simulations of the extended model showed that the use of the face mask by humans who come in close proximity with camels, as a sole public health intervention strategy, significantly reduced human-to-camel and camel-to-human transmission of the disease, and this reduction depends on the efficacy and coverage of the mask type used in the community. For instance, if surgical masks are prioritized, the disease can be eliminated in both the human and camel population if at least 45% of individuals who have close contact with camels wear them consistently. The simulations further showed that while vaccinating humans as a sole intervention strategy only had marginal impact in reducing the disease burden in the human population, an intervention strategy based on vaccinating camels only resulted in a significant reduction in the disease burden in camels (and, consequently, in humans as well). Thus, this study suggests that attention should be focused on effectively combating the disease in the camel population, rather than in the human population. Furthermore, the extended model was used to simulate a hybrid strategy, which combined vaccination of both humans and camels as well as the use of face masks by humans. This simulation showed a marked reduction of the disease burden in both humans and camels, with an increasing effectiveness level of this intervention, in comparison to the baseline scenario or any of the aforementioned sole vaccination scenarios. In summary, this study showed that the prospect of the elimination of MERS-CoV-2 in the Kingdom of Saudi Arabia is promising using pharmaceutical (vaccination) and nonpharmaceutical (mask) intervention strategies, implemented in isolation or (preferably) in combination, that are focused on reducing the disease burden in the camel population.

References

[1]	A. M. Zaki, S. Van Boheemen, T. M. Bestebroer, A. D. M. E. Osterhaus, R. A. M. Fouchier, Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia, N. Engl. J. Med., 367 (2012), 1814–1820. https://doi.org/10.1056/NEJMoa1211721 doi: 10.1056/NEJMoa1211721
[2]	T. M. Malik, A. A. Alsaleh, A. B. Gumel, M. A. Safi, Optimal strategies for controlling the MERS coronavirus during a mass gathering, Global J. Pure Appl. Math., 11 (2015), 4831–4865.
[3]	J. A. Tawfiq, C. A. H. Smallwood, K. G. Arbuthnott, M. S. K. Malik, M. Barbeschi, Z. A. Memish, Emerging respiratory and novel coronavirus 2012 infections and mass gatherings, EMHJ-East. Mediterr. Health J., 19 (2013), S48–S54. https://doi.org/10.26719/2013.19.supp1.S48 doi: 10.26719/2013.19.supp1.S48
[4]	A. Alatawi, Mathematical Assessment of the Transmission Dynamics and Control of MERS-CoV and SARS-CoV-2 in the Kingdom of Saudi Arabia, PhD thesis, Arizona State University, 2023.
[5]	J. Min, E. Cella, M. Ciccozzi, A. Pelosi, M. Salemi, M. Prosperi, The global spread of middle east respiratory syndrome: an analysis fusing traditional epidemiological tracing and molecular phylodynamics, Global Health Res. Policy, 1 (2016), 1–14. https://doi.org/10.1186/s41256-016-0014-7 doi: 10.1186/s41256-016-0014-7
[6]	K. P. Devakumar, MERS Outbreaks Data 2012–2019, Available from: https://www.kaggle.com/datasets/imdevskp/mers-outbreak-dataset-20122019.
[7]	World Health Organization, Middle East Respiratory Syndrome: Global Summary and Assessment of Risk, 2022. Available from: https://iris.who.int/bitstream/handle/10665/364525/WHO-MERS-RA-2022.1-eng.pdf.
[8]	ARAB NEWS, Saudi Arabia: Hajj 2020 to Be Held with Limited Number of Pilgrims, 2023. Available from: https://www.arabnews.com/node/1693856/saudi-arabia.
[9]	S. Gazette, International Camel Conference to be Held to Utilize Products, Stimulate Investment, 2021. Available from: https://saudigazette.com.sa/article/610500.
[10]	AlARABIYA news, Camel Club, 2023. Available from: https://english.alarabiya.net/views/2024/05/02/camel-racing-an-enduring-staple-of-arabian-gulf-sports-scene-now-and-in-the-future.
[11]	F. A. Rabi, M. S. A. Zoubi, G. A. Kasasbeh, D. M. Salameh, A. D. A. Nasser, SARS-CoV-2 and coronavirus disease 2019: what we know so far, Pathogens, 9 (2020), 231. https://doi.org/10.3390/pathogens9030231 doi: 10.3390/pathogens9030231
[12]	A. B. Gumel, E. A. Iboi, C. N. Ngonghala, E. H. Elbasha, A primer on using mathematics to understand COVID-19 dynamics: Modeling, analysis and simulations, Infect. Dis. Modell., 6 (2021), 148–168. https://doi.org/10.1016/j.idm.2020.11.005 doi: 10.1016/j.idm.2020.11.005
[13]	W. Li, Z. Shi, M. Yu, W. Ren, C. Smith, J. H. Epstein, et al., Bats are natural reservoirs of SARS-like coronaviruses, Science, 310 (2005), 676–679. https://doi.org/10.1126/science.1118391 doi: 10.1126/science.1118391
[14]	N. L. Ithete, S. Stoffberg, V. M. Corman, V. M. Cottontail, L. R. Richards, M. C. Schoeman, et al., Close relative of human middle east respiratory syndrome coronavirus in bat, South Africa, Emerging Infect. Dis., 19 (2013), 1697. https://doi.org/10.3201/eid1910.130946 doi: 10.3201/eid1910.130946
[15]	G. Chowell, S. Blumberg, L. Simonsen, M. A. Miller, C. Viboud, Synthesizing data and models for the spread of MERS-CoV, 2013: key role of index cases and hospital transmission, Epidemics, 9 (2014), 40–51. https://doi.org/10.1016/j.epidem.2014.09.011 doi: 10.1016/j.epidem.2014.09.011
[16]	T. A. Aljasim, A. Almasoud, H. A. Aljami, M. W. Alenazi, S. A. Alsagaby, A. N. Alsaleh, et al., High rate of circulating MERS-CoV in dromedary camels at slaughterhouses in Riyadh, 2019, Viruses, 12 (2020), 1215. https://doi.org/10.3390/v12111215 doi: 10.3390/v12111215
[17]	M. E. Killerby, H. M. Biggs, C. M. Midgley, S. I. Gerber, J. T. Watson, Middle east respiratory syndrome coronavirus transmission, Emerging Infect. Dis., 26 (2020), 191. https://doi.org/10.3201/eid2602.190697 doi: 10.3201/eid2602.190697
[18]	M. G. Hemida, A. Alnaeem, Some one health based control strategies for the middle east respiratory syndrome coronavirus, One Health, 8 (2019), 100102. https://doi.org/10.1016/j.onehlt.2019.100102 doi: 10.1016/j.onehlt.2019.100102
[19]	A. S. Omrani, J. A. Al-Tawfiq, Z. A. Memish, Middle east respiratory syndrome coronavirus (MERS-CoV): animal to human interaction, Pathog. Global Health, 109 (2015), 354–362. https://doi.org/10.1080/20477724.2015.1122852 doi: 10.1080/20477724.2015.1122852
[20]	Nature, Did Pangolins Spread the China Coronavirus to People, 2023. Available from: https://www.nature.com/articles/d41586-020-00364-2.
[21]	M. G. Hemida, R. A. Perera, P. Wang, M. A. Alhammadi, L. Y. Siu, M. Li, et al., Middle east respiratory syndrome (MERS) coronavirus seroprevalence in domestic livestock in Saudi Arabia, 2010 to 2013, Eurosurveillance, 18 (2013), 20659. https://doi.org/10.2807/1560-7917.ES2013.18.50.20659 doi: 10.2807/1560-7917.ES2013.18.50.20659
[22]	A. Mostafa, A. Kandeil, M. Shehata, R. E. Shesheny, A. M. Samy, G. Kayali, et al., Middle east respiratory syndrome coronavirus (MERS-CoV): State of the science, Microorganisms, 8 (2020), 991. https://doi.org/10.3390/microorganisms8070991 doi: 10.3390/microorganisms8070991
[23]	N. Van Doremalen, T. Bushmaker, V. J. Munster, Stability of middle east respiratory syndrome coronavirus (MERS-CoV) under different environmental conditions, Eurosurveillance, 18 (2013), 20590. https://doi.org/10.2807/1560-7917.ES2013.18.38.20590 doi: 10.2807/1560-7917.ES2013.18.38.20590
[24]	M. G. Hemida, A. Al-Naeem, R. A. P. M. Perera, A. W. H. Chin, L. L. M. Poon, M. Peiris, Lack of middle east respiratory syndrome coronavirus transmission from infected camels, Emerging Infect. Dis., 21 (2015), 699. https://doi.org/10.3201/eid2104.141949 doi: 10.3201/eid2104.141949
[25]	R. Conzade, R. Grant, M. R. Malik, A. Elkholy, M. Elhakim, D. Samhouri, et al., Reported direct and indirect contact with dromedary camels among laboratory-confirmed MERS-CoV cases, Viruses, 10 (2018), 425. https://doi.org/10.3390/v10080425 doi: 10.3390/v10080425
[26]	D. R. Adney, N. van Doremalen, V. R. Brown, T. Bushmaker, D. Scott, E. de Wit, et al., Replication and shedding of MERS-CoV in upper respiratory tract of inoculated dromedary camels, Emerging Infect. Dis., 20 (2014), 1999. https://doi.org/10.3201/eid2012.141280 doi: 10.3201/eid2012.141280
[27]	D. R. Adney, L. Wang, N. Van Doremalen, W. Shi, Y. Zhang, W. Kong, et al., Efficacy of an adjuvanted middle east respiratory syndrome coronavirus spike protein vaccine in dromedary camels and alpacas, Viruses, 11 (2019), 212. https://doi.org/10.3390/v11030212 doi: 10.3390/v11030212
[28]	I. Ghosh, S. K. S. Nadim, J. Chattopadhyay, Zoonotic MERS-CoV transmission: modeling, backward bifurcation and optimal control analysis, Nonlinear Dyn., 103 (2021), 2973–2992. https://doi.org/10.1007/s11071-021-06266-w doi: 10.1007/s11071-021-06266-w
[29]	J. A. Al-Tawfiq, Z. A. Memish, Middle east respiratory syndrome coronavirus: epidemiology and disease control measures, Infect. Drug Resist., 7 (2014), 281. https://doi.org/10.2147/IDR.S51283 doi: 10.2147/IDR.S51283
[30]	D. S. Hui, E. I. Azhar, Y. J. Kim, Z. A. Memish, M. Oh, A. Zumla, Middle east respiratory syndrome coronavirus: risk factors and determinants of primary, household, and nosocomial transmission, Lancet Infect. Dis., 18 (2018), e217–e227. https://doi.org/10.1016/S1473-3099(18)30127-0 doi: 10.1016/S1473-3099(18)30127-0
[31]	M. Tahir, S. I. A. Shah, G. Zaman, T. Khan, A dynamic compartmental mathematical model describing the transmissibility of MERS-CoV virus in public, Punjab Univ. J. Math., 51 (2020).
[32]	Z. A. Memish, A. I. Zumla, A. Assiri, Middle east respiratory syndrome coronavirus infections in health care workers, N. Engl. J. Med., 369 (2013), 884–886. https://doi.org/10.1056/NEJMc1308698 doi: 10.1056/NEJMc1308698
[33]	A. R. Zhang, W. Q. Shi, K. Liu, X. L. Li, M. J. Liu, W. H. Zhang, et al., Epidemiology and evolution of middle east respiratory syndrome coronavirus, 2012–2020, Infect. Dis. Poverty, 10 (2021), 1–13.
[34]	Z. Wu, D. Harrich, Z. Li, D. Hu, D. Li, The unique features of SARS-CoV-2 transmission: Comparison with SARS-CoV, MERS-CoV and 2009 H1N1 pandemic influenza virus, Rev. Med. Virol., 31 (2021), e2171. https://doi.org/10.1002/rmv.2171 doi: 10.1002/rmv.2171
[35]	N. C. Peeri, N. Shrestha, M. S. Rahman, R. Zaki, Z. Tan, S. Bibi, et al., The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned, Int. J. Epidemiol., 49 (2020), 717–726.
[36]	V. C. C. Cheng, K. K. W. To, H. Tse, I. F. N. Hung, K. Y. Yuen, Two years after pandemic influenza a/2009/H1N1: what have we learned, Clin. Microbiol. Rev., 25 (2012), 223–263. https://doi.org/10.1128/CMR.05012-11 doi: 10.1128/CMR.05012-11
[37]	E. A. Nardell, R. R. Nathavitharana, Airborne spread of SARS-CoV-2 and a potential role for air disinfection, JAMA, 324 (2020), 141–142. https://doi.org/10.1001/jama.2020.7603 doi: 10.1001/jama.2020.7603
[38]	S. Safdar, A. B. Gumel, Mathematical assessment of the role of interventions against SARS-CoV-2, in Mathematics of Public Health: Mathematical Modelling from the Next Generation, (2023), 243–294. https://doi.org/10.1007/978-3-031-40805-2_10
[39]	B. Ganesh, T. Rajakumar, M. Manikandan, J. Nagaraj, A. Santhakumar, A. Elangovan, et al., Epidemiology and pathobiology of SARS-CoV-2 (COVID-19) in comparison with SARS, MERS: An updated overview of current knowledge and future perspectives, Clin. Epidemiol. Global Health, 10 (2021), 100694.
[40]	A. Zumla, D. S. Hui, S. Perlman, Middle east respiratory syndrome, Lancet, 386 (2015), 995–1007. https://doi.org/10.1016/S0140-6736(15)60454-8 doi: 10.1016/S0140-6736(15)60454-8
[41]	E. I. Azhar, S. A. El-Kafrawy, S. A. Farraj, A. M. Hassan, M. S. Al-Saeed, A. M. Hashem, et al., Evidence for camel-to-human transmission of MERS coronavirus, N. Engl. J. Med., 370 (2014), 2499–2505. https://doi.org/10.1056/NEJMoa1401505 doi: 10.1056/NEJMoa1401505
[42]	J. S. Chung, M. L. Ling, W. H. Seto, B. S. P. Ang, P. A. Tambyah, Debate on MERS-CoV respiratory precautions: surgical mask or N95 respirators, Singapore Med. J., 55 (2014), 294. https://doi.org/10.11622/smedj.2014076 doi: 10.11622/smedj.2014076
[43]	A. M. Patil, J. R. Göthert, V. Khairnar, Emergence, transmission, and potential therapeutic targets for the COVID-19 pandemic associated with the SARS-CoV-2, Cell Physiol. Biochem., 54 (2020), 767–790. https://doi.org/10.33594/000000254 doi: 10.33594/000000254
[44]	H. H. Balkhy, T. H. Alenazi, M. M. Alshamrani, H. Baffoe-Bonnie, Y. Arabi, R. Hijazi, et al., Description of a hospital outbreak of middle east respiratory syndrome in a large tertiary care hospital in Saudi Arabia, Infect. Control Hosp. Epidemiol., 37 (2016), 1147–1155. https://doi.org/10.1017/ice.2016.132 doi: 10.1017/ice.2016.132
[45]	I. K. Oboho, S. M. Tomczyk, A. M. Al-Asmari, A. A. Banjar, H. Al-Mugti, M. S. Aloraini, et al., 2014 MERS-CoV outbreak in jeddah—a link to health care facilities, N. Engl. J. Med., 372 (2015), 846–854. https://doi.org/10.1056/NEJMoa1408636 doi: 10.1056/NEJMoa1408636
[46]	J. Liu, W. Xie, Y. Wang, Y. Xiong, S. Chen, J. Han, et al., A comparative overview of COVID-19, MERS and SARS, Int. J. Surg., 81 (2020), 1–8. https://doi.org/10.1016/j.ijsu.2020.07.032 doi: 10.1016/j.ijsu.2020.07.032
[47]	N. K. Alharbi, O. H. Ibrahim, A. Alhafufi, S. Kasem, A. Aldowerij, R. Albrahim, et al., Challenge infection model for mers-cov based on naturally infected camels, Virol. J., 17 (2020), 1–7. https://doi.org/10.1186/s12985-020-01347-5 doi: 10.1186/s12985-020-01347-5
[48]	S. S. Sohrab, S. A. El-Kafrawy, Z. Mirza, A. M. Hassan, F. Alsaqaf, E. I. Azhar, Computational design and experimental evaluation of MERS-CoV sirnas in selected cell lines, Diagnostics, 13 (2023), 151. https://doi.org/10.3390/diagnostics13010151 doi: 10.3390/diagnostics13010151
[49]	N. K. Alharbi, F. Aljamaan, H. A. Aljami, M. W. Alenazi, H. Albalawi, A. Almasoud, et al., Immunogenicity of high-dose MAV-based MERS vaccine candidate in mice and camels, Vaccines, 10 (2022), 1330. https://doi.org/10.3390/vaccines10081330 doi: 10.3390/vaccines10081330
[50]	Y. Zhou, S. Jiang, L. Du, Prospects for a MERS-CoV spike vaccine, Expert Rev. Vaccines, 17 (2018), 677–686. https://doi.org/10.1080/14760584.2018.1506702 doi: 10.1080/14760584.2018.1506702
[51]	B. L. Haagmans, J. M. A. Van Den Brand, V. S. Raj, A. Volz, P. Wohlsein, S. L. Smits, et al., An orthopoxvirus-based vaccine reduces virus excretion after MERS-CoV infection in dromedary camels, Science, 351 (2016), 77–81. https://doi.org/10.1126/science.aad1283 doi: 10.1126/science.aad1283
[52]	M. Kandeel, A. I. Al-Mubarak, Camel viral diseases: Current diagnostic, therapeutic, and preventive strategies, Front. Vet. Sci., 9 (2022), 915475. https://doi.org/10.3389/fvets.2022.915475 doi: 10.3389/fvets.2022.915475
[53]	N. K. Alharbi, Vaccines against middle east respiratory syndrome coronavirus for humans and camels, Rev. Med. Virol., 27 (2017), e1917. https://doi.org/10.1002/rmv.1917 doi: 10.1002/rmv.1917
[54]	Inc. INOVIO Pharmaceuticals, Inovio Doses First Participant in Phase 2 Trial for Its DNA Vaccine Against Middle East Respiratory Syndrome (MERS), A Coronavirus Disease, 2023. Available from: https://ir.inovio.com/news-releases/news-releases-details/2021/INOVIO-Doses-First-Participant-in-Phase-2-Trial-for-its-DNA-Vaccine-Against-Middle-East-Respiratory-Syndrome-MERS-a-Coronavirus-Disease/default.aspx.
[55]	I. M. Mackay, K. E. Arden, MERS coronavirus: diagnostics, epidemiology and transmission, Virol. J., 12 (2015), 1–21. https://doi.org/10.1186/s12985-015-0439-5 doi: 10.1186/s12985-015-0439-5
[56]	Inc. Johnson & Johnson Services, Johnson & Johnson Announces New Collaboration to Advance Novel Vaccine for MERS, 2023. Available from: https://www.jnj.com/media-center/press-releases/johnson-johnson-announces-new-collaboration-to-advance-novel-vaccine-for-mers.
[57]	G. M. Warimwe, J. Gesharisha, B. V. Carr, S. Otieno, K. Otingah, D. Wright, et al., Chimpanzee adenovirus vaccine provides multispecies protection against rift valley fever, Sci. Rep., 6 (2016), 1–7. https://doi.org/10.1038/srep20617 doi: 10.1038/srep20617
[58]	T. Sardar, I. Ghosh, X. Rodó, J. Chattopadhyay, A realistic two-strain model for MERS-CoV infection uncovers the high risk for epidemic propagation, PLoS Negl.Trop. Dis., 14 (2020), e0008065. https://doi.org/10.1371/journal.pntd.0008065 doi: 10.1371/journal.pntd.0008065
[59]	T. Oraby, M. G. Tyshenko, H. H. Balkhy, Y. Tasnif, A. Quiroz-Gaspar, Z. Mohamed, et al., Analysis of the healthcare MERS-CoV outbreak in king abdulaziz medical center, Riyadh, Saudi Arabia, June–August 2015 using a SEIR ward transmission model, Int. J. Environ. Res. Public Health, 17 (2020), 2936. https://doi.org/10.3390/ijerph17082936 doi: 10.3390/ijerph17082936
[60]	S. Cauchemez, P. Nouvellet, A. Cori, T. Jombart, T. Garske, H. Clapham, et al., Unraveling the drivers of MERS-CoV transmission, Proc. Natl. Acad. Sci., 113 (2016), 9081–9086. https://doi.org/10.1073/pnas.1519235113 doi: 10.1073/pnas.1519235113
[61]	M. John, H. Shaiba, Main factors influencing recovery in MERS CoV patients using machine learning, J. Infect. Public Health, 12 (2019), 700–704. https://doi.org/10.1016/j.jiph.2019.03.020 doi: 10.1016/j.jiph.2019.03.020
[62]	S. Hussain, O. Tunç, G. ur Rahman, H. Khan, E. Nadia, Mathematical analysis of stochastic epidemic model of MERS-corona & application of ergodic theory, Math. Comput. Simul., 207 (2023), 130–150. https://doi.org/10.1016/j.matcom.2022.12.023 doi: 10.1016/j.matcom.2022.12.023
[63]	Q. Lin, A. P. Y. Chiu, S. Zhao, D. He, Modeling the spread of middle east respiratory syndrome coronavirus in Saudi Arabia, Stat. Methods Med. Res., 27 (2018), 1968–1978. https://doi.org/10.1177/0962280217746442 doi: 10.1177/0962280217746442
[64]	C. Poletto, V. Colizza, P. Y. Boëlle, Quantifying spatiotemporal heterogeneity of MERS-CoV transmission in the middle east region: A combined modelling approach, Epidemics, 15 (2016), 1–9. https://doi.org/10.1016/j.epidem.2015.12.001 doi: 10.1016/j.epidem.2015.12.001
[65]	B. Fatima, M. A. Alqudah, G. Zaman, F. Jarad, T. Abdeljawad, Modeling the transmission dynamics of middle eastern respiratory syndrome coronavirus with the impact of media coverage, Results Phys., 24 (2021), 104053. https://doi.org/10.1016/j.rinp.2021.104053 doi: 10.1016/j.rinp.2021.104053
[66]	J. Rui, Q. Wang, J. Lv, B. Zhao, Q. Hu, H. Du, et al., The transmission dynamics of middle east respiratory syndrome coronavirus, Travel Med. Infect. Dis., 45 (2022), 102243. https://doi.org/10.1016/j.tmaid.2021.102243 doi: 10.1016/j.tmaid.2021.102243
[67]	J. Lee, G. Chowell, E. Jung, A dynamic compartmental model for the middle east respiratory syndrome outbreak in the republic of Korea: a retrospective analysis on control interventions and superspreading events, J. Theor. Biol., 408 (2016), 118–126. https://doi.org/10.1016/j.jtbi.2016.08.009 doi: 10.1016/j.jtbi.2016.08.009
[68]	W. Jansen, V. Lakshmikantham, S. Leela, A. A. Martynyuk, Stability Analysis of Nonlinear Systems, Marcel Dekker inc., 1995.
[69]	A. B. Gumel, C. C. McCluskey, P. van den Driessche, Mathematical study of a staged-progression HIV model with imperfect vaccine, Bull. Math. Biol., 68 (2006), 2105–2128. https://doi.org/10.1007/s11538-006-9095-7 doi: 10.1007/s11538-006-9095-7
[70]	J. Mohammed-Awel, E. A. Iboi, A. B. Gumel, Insecticide resistance and malaria control: A genetics-epidemiology modeling approach, Math. Biosci., 325 (2020), 108368. https://doi.org/10.1016/j.mbs.2020.108368 doi: 10.1016/j.mbs.2020.108368
[71]	S. M. Garba, J. M. S. Lubuma, B. Tsanou, Modeling the transmission dynamics of the COVID-19 pandemic in South Africa, Math. Biosci., 328 (2020), 108441. https://doi.org/10.1016/j.mbs.2020.108441 doi: 10.1016/j.mbs.2020.108441
[72]	H. R. Thieme, Mathematics in Population Biology, Princeton University Press, 2018.
[73]	P. Van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
[74]	O. Diekmann, J. A. P. Heesterbeek, J. A. J. Metz, On the definition and the computation of the basic reproduction ratio $R_0$ in models for infectious diseases in heterogeneous populations, J. Math. Biol., 28 (1990), 365–382. https://doi.org/10.1007/BF00178324 doi: 10.1007/BF00178324
[75]	K. O. Okuneye, J. X. Velasco-Hernandez, A. B. Gumel, The "unholy" chikungunya–dengue–Zika trinity: a theoretical analysis, J. Biol. Syst., 25 (2017), 545–585. https://doi.org/10.1142/S0218339017400046 doi: 10.1142/S0218339017400046
[76]	H. T. Banks, M. Davidian, J. R. Samuels, K. L. Sutton, An inverse problem statistical methodology summary, in Mathematical and Statistical Estimation Approaches in Epidemiology, (2009), 249–302. https://doi.org/10.1007/978-90-481-2313-1
[77]	G. Chowell, Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A primer for parameter uncertainty, identifiability, and forecasts, Infect. Dis. Modell., 2 (2017), 379–398. https://doi.org/10.1016/j.idm.2017.08.001 doi: 10.1016/j.idm.2017.08.001
[78]	C. N. Ngonghala, E. Iboi, S. Eikenberry, M. Scotch, C. R. MacIntyre, M. H. Bonds, et al., Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel coronavirus, Math. Biosci., 325 (2020), 108364. https://doi.org/10.1016/j.mbs.2020.108364 doi: 10.1016/j.mbs.2020.108364
[79]	S. M. Blower, H. Dowlatabadi, Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example, Int. Stat. Rev., 62 (1994), 229–243. https://doi.org/10.2307/1403510 doi: 10.2307/1403510
[80]	S. Marino, I. B. Hogue, C. J. Ray, D. E. Kirschner, A methodology for performing global uncertainty and sensitivity analysis in systems biology, J. Theor. Biol., 254 (2008), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 doi: 10.1016/j.jtbi.2008.04.011
[81]	S. J. Ryan, A. McNally, L. R. Johnson, E. A. Mordecai, T. Ben-Horin, K. Paaijmans, et al., Mapping physiological suitability limits for malaria in Africa under climate change, Vector-Borne and Zoonotic Dis., 15 (2015), 718–725. https://doi.org/10.1089/vbz.2015.1822 doi: 10.1089/vbz.2015.1822
[82]	J. Wu, R. Dhingra, M. Gambhir, J. V. Remais, Sensitivity analysis of infectious disease models: methods, advances and their application, J. R. Soc. Interface, 10 (2013), 20121018. https://doi.org/10.1098/rsif.2012.1018 doi: 10.1098/rsif.2012.1018
[83]	R. G. McLeod, J. F. Brewster, A. B. Gumel, D. A. Slonowsky, Sensitivity and uncertainty analyses for a SARS model with time-varying inputs and outputs, Math. Biosci. Eng., 3 (2006), 527. https://doi.org/10.3934/mbe.2006.3.527 doi: 10.3934/mbe.2006.3.527
[84]	J. Carboni, D. Gatelli, R. Lika, A. Saltelli, The role of sensitivity analysis in ecological modeling, Ecol. Model., 203 (2006), 167–182. https://doi.org/10.1016/j.ecolmodel.2005.10.045 doi: 10.1016/j.ecolmodel.2005.10.045
[85]	E. Iboi, A. Richardson, R. Ruffin, D. Ingram, J. Clark, J. Hawkins, et al., Impact of public health education program on the novel coronavirus outbreak in the United States, Front. Public Health, 9 (2021), 630974. https://doi.org/10.3389/fpubh.2021.630974 doi: 10.3389/fpubh.2021.630974
[86]	World Population Review, Saudi Arabia Population 2021, 2022. Available from: https://worldpopulationreview.com/countries/saudi-arabia-population.
[87]	The World Bank—Data, Life Expectancy at Birth, Total (Years)–Saudi Arabia, 2022. Available from: https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations = SA-AD
[88]	WLE, Animal Life Expectancy, 2021. Available from: https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations = SA-AD
[89]	S. Safdar, C. N. Ngonghala, A. Gumel, Mathematical assessment of the role of waning and boosting immunity against the BA. 1 Omicron variant in the United States, 20 (2023), 179–212. https://doi.org/10.3934/mbe.2023009
[90]	J. E. Park, S. Jung, A. Kim, MERS transmission and risk factors: a systematic review, BMC Public Health, 18 (2018), 1–15. https://doi.org/10.1186/s12889-018-5484-8 doi: 10.1186/s12889-018-5484-8
[91]	X. Jiang, S. Rayner, M. H. Luo, Does SARS-CoV-2 has a longer incubation period than SARS and MERS, J. Med. Virol., 92 (2020), 476–478. https://doi.org/10.1002/jmv.25708 doi: 10.1002/jmv.25708
[92]	Centers for Disease Control and Prevention (CDC), MERS coronavirus in dromedary camel herd, Saudi Arabia, Emerging Infect. Dis., 20 (2022), 1231–1234. https://doi.org/10.3201/eid2007.140571 doi: 10.3201/eid2007.140571
[93]	C. N. Ngonghala, H. B. Taboe, S. Safdar, A. B. Gumel, Unraveling the dynamics of the Omicron and Delta variants of the 2019 coronavirus in the presence of vaccination, mask usage, and antiviral treatment, Appl. Math. Modell., 114 (2023), 447–465. https://doi.org/10.1016/j.apm.2022.09.017 doi: 10.1016/j.apm.2022.09.017
[94]	A. B. Gumel, E. A. Iboi, C. N. Ngonghala, G. A. Ngwa, Toward achieving a vaccine-derived herd immunity threshold for COVID-19 in the US, Front. Public Health, 9 (2021), 709369. https://doi.org/10.3389/fpubh.2021.709369 doi: 10.3389/fpubh.2021.709369
[95]	A. B. Gumel, E. A. Iboi, C. N. Ngonghala, G. A. Ngwa, Mathematical assessment of the roles of vaccination and non-pharmaceutical interventions on COVID-19 dynamics: a multigroup modeling approach, 2020 (2020).
[96]	M. G. Hemida, A. Elmoslemany, F. Al-Hizab, A. Alnaeem, F. Almathen, B. Faye, et al., Dromedary camels and the transmission of middle east respiratory syndrome coronavirus (MERS-CoV), Transboundary Emerging Dis., 64 (2017), 344–353. https://doi.org/10.1111/tbed.12401 doi: 10.1111/tbed.12401
[97]	S. E. Eikenberry, M. Mancuso, E. Iboi, T. Phan, K. Eikenberry, Y. Kuang, et al., To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic, Infect. Dis. modell., 5 (2020), 293–308. https://doi.org/10.1016/j.idm.2020.04.001 doi: 10.1016/j.idm.2020.04.001

Reader Comments

Your name:*

Email:*
© 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)