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Chen B, Zhao Y, Jin Z, He D, Li H. Twice evasions of Omicron variants explain the temporal patterns in six Asian and Oceanic countries. BMC Infect Dis 2023; 23:25. [PMID: 36639649 PMCID: PMC9839219 DOI: 10.1186/s12879-023-07984-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 01/04/2023] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND The ongoing coronavirus 2019 (COVID-19) pandemic has emerged and caused multiple pandemic waves in the following six countries: India, Indonesia, Nepal, Malaysia, Bangladesh and Myanmar. Some of the countries have been much less studied in this devastating pandemic. This study aims to assess the impact of the Omicron variant in these six countries and estimate the infection fatality rate (IFR) and the reproduction number [Formula: see text] in these six South Asia, Southeast Asia and Oceania countries. METHODS We propose a Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Death-Recovered model with a time-varying transmission rate [Formula: see text] to fit the multiple waves of the COVID-19 pandemic and to estimate the IFR and [Formula: see text] in the aforementioned six countries. The level of immune evasion and the intrinsic transmissibility advantage of the Omicron variant are also considered in this model. RESULTS We fit our model to the reported deaths well. We estimate the IFR (in the range of 0.016 to 0.136%) and the reproduction number [Formula: see text] (in the range of 0 to 9) in the six countries. Multiple pandemic waves in each country were observed in our simulation results. CONCLUSIONS The invasion of the Omicron variant caused the new pandemic waves in the six countries. The higher [Formula: see text] suggests the intrinsic transmissibility advantage of the Omicron variant. Our model simulation forecast implies that the Omicron pandemic wave may be mitigated due to the increasing immunized population and vaccine coverage.
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Affiliation(s)
- Boqiang Chen
- grid.16890.360000 0004 1764 6123Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Yanji Zhao
- grid.16890.360000 0004 1764 6123Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Zhen Jin
- grid.163032.50000 0004 1760 2008Complex Systems Research Center, Shanxi University, Taiyuan, China
| | - Daihai He
- grid.16890.360000 0004 1764 6123Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Huaichen Li
- grid.460018.b0000 0004 1769 9639Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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Touchton M, Wampler B. Democratizing Public Health: Participatory Policymaking Institutions, Mosquito Control, and Zika in the Americas. Trop Med Infect Dis 2023; 8:tropicalmed8010038. [PMID: 36668945 PMCID: PMC9865320 DOI: 10.3390/tropicalmed8010038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 01/03/2023] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
The Zika virus is a mosquito-borne virus spread primarily by Aedes mosquitoes. Zika cases have been detected throughout the mosquito's range, with an epidemic occurring from 2015 to 2017 in Brazil. Many Zika cases are mild or asymptomatic, but infections in pregnant women can cause microcephaly in children, and a small percentage of cases result in Guillan-Barré syndrome. There is currently little systematic information surrounding the municipal spread of the Zika Virus in Brazil. This article uses coarsened exact matching with negative binomial estimation and ordinary least squares estimation to assess the determinants of Zika incidence across the ~280,000 cases confirmed and recorded by Brazil's Ministry of Health in 2016 and 2017. These data come from Freedom of Information Act (FOIA) requests in Brazil and have not been published. We use data on the universe of individual Zika cases in Brazil and Geographic Information Systems (GIS) software to examine the virus at the municipal level across 5570 municipalities and construct a unique, unusually rich dataset covering daily Zika transmission. Additionally, our dataset includes corresponding local data on democratic governance, mosquito control efforts, and environmental conditions to estimate their relationship to Zika transmission. The results demonstrate that the presence of subnational democratic, participatory policymaking institutions and high levels of local state capacity are associated with low rates of Zika contraction. These models control for local healthcare spending and economic conditions, among other factors, that also influence Zika contraction rates. In turn, these findings provide a better understanding of what works for local health governance and mosquito control and makes important data public so that scholars and practitioners can perform their own analyses. Stronger models of Zika transmission will then inform mosquito abatement efforts across the Global South, as well as provide a blueprint for combatting Dengue fever, which is also transmitted by Aedes mosquitoes.
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Affiliation(s)
- Michael Touchton
- Department of Political Science, University of Miami, Coral Gables, FL 33146, USA
- Faculty Lead for Global Health, Institute for Advanced Studies of the Americas, University of Miami, Coral Gables, FL 33146, USA
- Correspondence:
| | - Brian Wampler
- President’s Office of Public Engagement, Boise State University, Boise, ID 83725, USA
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Fisher A, Xu H, He D, Wang X. Effects of vaccination on mitigating COVID-19 outbreaks: a conceptual modeling approach. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:4816-4837. [PMID: 36896524 DOI: 10.3934/mbe.2023223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
This paper is devoted to investigating the impact of vaccination on mitigating COVID-19 outbreaks. In this work, we propose a compartmental epidemic ordinary differential equation model, which extends the previous so-called SEIRD model [1,2,3,4] by incorporating the birth and death of the population, disease-induced mortality and waning immunity, and adding a vaccinated compartment to account for vaccination. Firstly, we perform a mathematical analysis for this model in a special case where the disease transmission is homogeneous and vaccination program is periodic in time. In particular, we define the basic reproduction number $ \mathcal{R}_0 $ for this system and establish a threshold type of result on the global dynamics in terms of $ \mathcal{R}_0 $. Secondly, we fit our model into multiple COVID-19 waves in four locations including Hong Kong, Singapore, Japan, and South Korea and then forecast the trend of COVID-19 by the end of 2022. Finally, we study the effects of vaccination again the ongoing pandemic by numerically computing the basic reproduction number $ \mathcal{R}_0 $ under different vaccination programs. Our findings indicate that the fourth dose among the high-risk group is likely needed by the end of the year.
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Affiliation(s)
- Allison Fisher
- Department of Mathematics and Statistics, Washington State University, Pullman, WA 99164, USA
| | - Hainan Xu
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Daihai He
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Xueying Wang
- Department of Mathematics and Statistics, Washington State University, Pullman, WA 99164, USA
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4
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Musa SS, Wang X, Zhao S, Li S, Hussaini N, Wang W, He D. The Heterogeneous Severity of COVID-19 in African Countries: A Modeling Approach. Bull Math Biol 2022; 84:32. [PMID: 35067773 PMCID: PMC8784278 DOI: 10.1007/s11538-022-00992-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 01/01/2022] [Indexed: 02/06/2023]
Abstract
The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number (\documentclass[12pt]{minimal}
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\begin{document}$${R}_{0}(t)$$\end{document}R0(t)) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher \documentclass[12pt]{minimal}
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\begin{document}$${R}_{0}(t)$$\end{document}R0(t) and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).
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Musa SS, Wang X, Zhao S, Li S, Hussaini N, Wang W, He D. The Heterogeneous Severity of COVID-19 in African Countries: A Modeling Approach. Bull Math Biol 2022. [PMID: 35067773 DOI: 10.21203/rs.3.rs-316589/v1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number ([Formula: see text]) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher [Formula: see text] and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).
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Affiliation(s)
- Salihu Sabiu Musa
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
- Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria
| | - Xueying Wang
- Department of Mathematics and Statistics, Washington State University, Pullman, WA, USA
| | - Shi Zhao
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
- Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China
| | - Shudong Li
- Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, 510006, China
| | - Nafiu Hussaini
- Department of Mathematical Sciences, Bayero University Kano, Kano, Nigeria
| | - Weiming Wang
- School of Mathematics and Statistics, Huaiyin Normal University, Huaian, 223300, China
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
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6
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Feng A, Obolski U, Stone L, He D. Modelling COVID-19 vaccine breakthrough infections in highly vaccinated Israel-The effects of waning immunity and third vaccination dose. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0001211. [PMID: 36962648 PMCID: PMC10021336 DOI: 10.1371/journal.pgph.0001211] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 10/09/2022] [Indexed: 11/11/2022]
Abstract
In August 2021, a major wave of the SARS-CoV-2 Delta variant erupted in the highly vaccinated population of Israel. The transmission advantage of the Delta variant enabled it to replace the Alpha variant in approximately two months. The outbreak led to an unexpectedly large proportion of breakthrough infections (BTI)-a phenomenon that received worldwide attention. Most of the Israeli population, especially those aged 60+, received their second dose of the vaccination four months before the invasion of the Delta variant. Hence, either the vaccine induced immunity dropped significantly or the Delta variant possesses immunity escaping abilities, or both. In this work, we model data obtained from the Israeli Ministry of Health, to help understand the epidemiological factors involved in the outbreak. We propose a mathematical model that captures a multitude of factors, including age structure, the time varying vaccine efficacy, time varying transmission rate, BTIs, reduced susceptibility and infectivity of vaccinated individuals, protection duration of the vaccine induced immunity, and the vaccine distribution. We fitted our model to COVID-19 cases among the vaccinated and unvaccinated, for <60 and 60+ age groups, and quantified the transmission rate, the vaccine efficacy over time and the impact of the third dose booster vaccine. The peak transmission rate of the Delta variant was found to be 2.14 times higher than that of the Alpha variant. The two-dose vaccine efficacy against infection dropped significantly from >90% to ~40% over 6 months. We further performed model simulations and quantified counterfactual scenarios examining what would happen if the booster had not been rolled out. We estimated that approximately 4.03 million infective cases (95%CI 3.19, 4.86) were prevented by vaccination overall, and 1.22 million infective cases (95%CI 0.89, 1.62) averted by the booster.
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Affiliation(s)
- Anyin Feng
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Uri Obolski
- School of Public Health, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Porter School of the Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Lewi Stone
- Mathematical Sciences, School of Science, RMIT University, Melbourne, Australia
- Biomathematics Unit, School of Zoology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Daihai He
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Future Food, The Hong Kong Polytechnic University, Hong Kong, China
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7
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Song H, Fan G, Zhao S, Li H, Huang Q, He D. Forecast of the COVID-19 trend in India: A simple modelling approach. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:9775-9786. [PMID: 34814368 DOI: 10.3934/mbe.2021479] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
By February 2021, the overall impact of the COVID-19 pandemic in India had been relatively mild in terms of total reported cases and deaths. Surprisingly, the second wave in early April becomes devastating and attracts worldwide attention. Multiple factors (e.g., Delta variants with increased transmissibility) could have driven the rapid growth of the epidemic in India and led to a large number of deaths within a short period. We aim to reconstruct the transmission rate, estimate the infection fatality rate and forecast the epidemic size. We download the reported COVID-19 mortality data in India and formulate a simple mathematical model with a flexible transmission rate. We use iterated filtering to fit our model to deaths data. We forecast the infection attack rate in a month ahead. Our model simulation matched the reported deaths well and is reasonably close to the results of the serological study. We forecast that the infection attack rate (IAR) could have reached 43% by July 24, 2021, under the current trend. Our estimated infection fatality rate is about 0.07%. Under the current trend, the IAR will likely reach a level of 43% by July 24, 2021. Our estimated infection fatality rate appears unusually low, which could be due to a low case to infection ratio reported in previous study. Our approach is readily applicable in other countries and with other types of data (e.g., excess deaths).
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Affiliation(s)
- Haitao Song
- Complex Systems Research Center, Shanxi University, Taiyuan 030006, China
| | - Guihong Fan
- Department of Mathematics, Columbus State University, Columbus 31907, USA
| | - Shi Zhao
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Huaichen Li
- Department of Pulmonary and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Qihua Huang
- School of Mathematical and Statistical Sciences, Southwest University, Chongqing 400715, China
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
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8
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A Zika Endemic Model for the Contribution of Multiple Transmission Routes. Bull Math Biol 2021; 83:111. [PMID: 34581872 DOI: 10.1007/s11538-021-00945-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 09/15/2021] [Indexed: 12/12/2022]
Abstract
Zika virus disease is a viral disease primarily transmitted to humans through the bite of infected female mosquitoes. Recent evidence indicates that the virus can also be sexually transmitted in hosts and vertically transmitted in vectors. In this paper, we propose a Zika model with three transmission routes, that is, vector-borne transmission between humans and mosquitoes, sexual transmission within humans and vertical transmission within mosquitoes. The basic reproduction number [Formula: see text] is computed and shown to be a sharp threshold quantity. Namely, the disease-free equilibrium is globally asymptotically stable as [Formula: see text], whereas there exists a unique endemic equilibrium which is globally asymptotically stable as [Formula: see text]. The relative contributions of each transmission route on the reproduction number, and the short- and long-term host infections are analyzed. Numerical simulations confirm that vectorial transmission contributes the most to the initial and subsequent transmission. The role of sexual transmission in the early phase of a Zika outbreak is greater than the long term, while vertical transmission is the opposite. Reducing mosquito bites is the most effective measure in lowering the risk of Zika virus infection.
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Shrinkage in serial intervals across transmission generations of COVID-19. J Theor Biol 2021; 529:110861. [PMID: 34390731 PMCID: PMC8356772 DOI: 10.1016/j.jtbi.2021.110861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 08/06/2021] [Accepted: 08/08/2021] [Indexed: 11/23/2022]
Abstract
One of the key epidemiological characteristics that shape the transmission of coronavirus disease 2019 (COVID-19) is the serial interval (SI). Although SI is commonly considered following a probability distribution at a population scale, recent studies reported a slight shrinkage (or contraction) of the mean of effective SI across transmission generations or over time. Here, we develop a likelihood-based statistical inference framework with truncation to explore the change in SI across transmission generations after adjusting the impacts of case isolation. The COVID-19 contact tracing surveillance data in Hong Kong are used for exemplification. We find that for COVID-19, the mean of individual SI is likely to shrink with a factor at 0.72 per generation (95%CI: 0.54, 0.96) as the transmission generation increases, where a threshold may exist as the lower boundary of this shrinking process. We speculate that one of the probable explanations for the shrinkage in SI might be an outcome due to the competition among multiple candidate infectors within the same case cluster. Thus, the nonpharmaceutical interventive strategies are crucially important to block the transmission chains, and mitigate the COVID-19 epidemic.
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Tang X, Musa SS, Zhao S, Mei S, He D. Using Proper Mean Generation Intervals in Modeling of COVID-19. Front Public Health 2021; 9:691262. [PMID: 34291032 PMCID: PMC8287506 DOI: 10.3389/fpubh.2021.691262] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 05/19/2021] [Indexed: 12/17/2022] Open
Abstract
In susceptible-exposed-infectious-recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of infection attack rate (AR) and control efficacy. We argue that it is important to use suitable epidemiological parameter values for proper estimation/prediction. Furthermore, we propose an epidemic model to assess the transmission dynamics of COVID-19 for Belgium, Israel, and the United Arab Emirates (UAE). We estimated a time-varying reproductive number [R0(t)] based on the COVID-19 deaths data and we found that Belgium has the highest AR followed by Israel and the UAE.
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Affiliation(s)
- Xiujuan Tang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Salihu S. Musa
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China
- Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria
| | - Shi Zhao
- The Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
- Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China
| | - Shujiang Mei
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Daihai He
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China
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Papaya Fruit Pulp and Resulting Lactic Fermented Pulp Exert Antiviral Activity against Zika Virus. Microorganisms 2020; 8:microorganisms8091257. [PMID: 32825246 PMCID: PMC7565477 DOI: 10.3390/microorganisms8091257] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 08/16/2020] [Accepted: 08/18/2020] [Indexed: 02/07/2023] Open
Abstract
There are a several emerging and re-emerging RNA viruses that are prevalent around the world for which there are no licensed vaccines or antiviral drugs. Zika virus (ZIKV) is an example of an emerging virus that has become a significant concern worldwide because of its association with severe congenital malformations and neurological disorders in adults. Several polyphenol-rich extracts from plants were used as nutraceuticals which exhibit potent in vitro antiviral effects. Here, we demonstrated that the papaya pulp extracted from Carica papaya fruit inhibits the infection of ZIKV in human cells without loss of cell viability. At the non-cytotoxic concentrations, papaya pulp extract has the ability to reduce the virus progeny production in ZIKV-infected human cells by at least 4-log, regardless of viral strains tested. Time-of-drug-addition assays revealed that papaya pulp extract interfered with the attachment of viral particles to the host cells. With a view of preserving the properties of papaya pulp over time, lactic fermentation based on the use of bacterial strains Weissella cibaria 64, Lactobacillus plantarum 75 and Leuconostoc pseudomesenteroides 56 was performed and the resulting fermented papaya pulp samples were tested on ZIKV. We found that lactic fermentation of papaya pulp causes a moderate loss of antiviral activity against ZIKV in a bacterial strain-dependent manner. Whereas IC50 of the papaya pulp extract was 0.3 mg/mL, we found that fermentation resulted in IC50 up to 4 mg/mL. We can conclude that papaya pulp possesses antiviral activity against ZIKV and the fermentation process has a moderate effect on the antiviral effect.
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