Susceptible Human Populations Research Articles

NUMERICAL ASSESSMENT OF SOME SEMI-ANALYTICAL TECHNIQUES FOR SOLVING A FRACTIONAL-ORDER LEPTOSPIROSIS MODEL

This research aims to apply and compare two semi-analytical techniques, the Variational Iterative Method (VIM) and the New Iterative Method (NIM), for solving a pre-formulated mathematical model of Fractional-order Leptospirosis. Leptospirosis is a significant bacterial infection affecting humans and animals. By implementing the VIM and NIM algorithms, numerical experiments are conducted to solve the leptospirosis model. Comparing the obtained findings demonstrates that VIM and NIM are effective semi-analytical methods for solving systems of fractional differential equations. Notably, our study unveils a crucial dynamic in the disease's spread. The application of VIM and NIM offers a refined depiction of the biological dynamics, highlighting that the susceptible human population gradually decreases, the infectious human population declines, the recovered human population increases, and a significant rise in the infected vector population is observed over time. This nuanced portrayal of the disease's dynamics is crucial for understanding the intricate interplay of Leptospirosis among human and vector populations. The study's outcomes contribute valuable insights into the applicability and performance of the methods in solving the Fractional Leptospirosis model. Results indicate rapid convergence and comparable outcomes for both methods.

The timeline of overseas imported cases acts as a strong indicator of dengue outbreak in mainland China.

The emergence of dengue viruses in new, susceptible human populations worldwide is increasingly influenced by a combination of local and global human movements and favorable environmental conditions. While various mathematical models have explored the impact of environmental factors on dengue outbreaks, the significant role of human mobility both internationally and domestically in transmitting the disease has been less frequently addressed. In this context, we introduce a modeling framework that integrates the effects of international travel-induced imported cases, climatic conditions, and local human movements to assess the spatiotemporal dynamics of dengue transmission. Utilizing the generation matrix method, we calculate the basic reproduction number and its sensitivity to various model parameters. Through numerical simulations using data on climate, human mobility, and reported dengue cases in mainland China, our model demonstrates a good agreement with observed data upon validation. Our findings reveal that while climatic conditions are a key driver for the rapid dengue transmission, human mobility plays a crucial role in its local spread. Importantly, the model highlights the significant impact of imported cases from overseas on the initiation of dengue outbreaks and their contribution to increasing the disease incidence rate by 34.6%. Furthermore, the analysis identifies that dengue cases originating from regions, such as Cambodia and Myanmar internationally, and Guangzhou and Xishuangbanna domestically, have the potential to significantly increase the disease burden in mainland China. These insights emphasize the critical need to include data on imported cases and domestic travel patterns in disease outbreak models to improve the precision of predictions, thereby enhancing dengue prevention, surveillance, and response strategies.

Phylogenetic analysis reveals a new introduction of Yellow Fever virus in São Paulo State, Brazil, 2023

Yellow Fever (YF) is a viral arbovirosis of Public Health importance. In Brazil, surveillance is focused mainly on detecting epizootic events of Platyrrhini. Herein, we compared the detection and phylogenetic analysis of YF virus in two neotropical primates (NTP), a Callithrix detected in the previous epidemic period (2016-2020), and a Callicebus nigrifons, showing a new introduction of YF in 2023. This paper illustrates the importance of joint actions of laboratory and field teams to ensure quick response to Public Health emergencies, such as the intensification of vaccination of susceptible human populations.

Leptospirosis Relative Risk Estimates based on Continuous-Time, Discrete-Space Stochastic SIR-L-SI Transmission Model

Leptospirosis is a re-emerging global disease that has become endemic in Malaysia. The transmissions usually occur between animals especially rats to rats and rats to humans. Since, it is an easily contractable disease that can be transmitted directly through contact with infected rat’s urine or indirectly from the environment such as via water and soil, it is very challenging to curb this disease from infecting humans. Poor understanding of the disease and lack of epidemiological data also made leptospirosis is difficult to control. To cope with this problem, a leptospirosis disease transmission model is developed to study the mechanism of leptospirosis disease spread over continuous-time that may help to predict future caused of an outbreak. This study aims to construct a continuous-time and discrete-space stochastic SIR-L-SI (Susceptible, Infected, Recovered Humans-Leptospires in the Environment-Susceptible, Infectious Rats) of leptospirosis disease transmission to estimate the risk involved. A simple method of asymptotic and numerical analyses is applied as an alternative approach for solving simultaneous differential equations in the leptospirosis SIR-L-SI transmission model. The application of the proposed model is demonstrated using leptospirosis data for Malaysia. The results of asymptotic behaviour and numerical analysis provide useful information about susceptible and infective rat and human populations as well as offer relative risk estimates that can be used as one of the control measures in identifying hot-spot areas for this disease.

Modeling and Analysis of an Age-Structured Malaria Model in the Sense of Atangana–Baleanu Fractional Operators

In this paper, integer- and fractional-order models are discussed to investigate the dynamics of malaria in a human host with a varied age distribution. A system of differential equation model with five human state variables and two mosquito state variables was examined. Preschool-age (0–5) and young-age individuals make up our model’s division of the human population. We investigated the existence of an area in which the model is both mathematically and epidemiologically well posed. According to the findings of our mathematical research, the disease-free equilibrium exists whenever the fundamental reproduction number R0 is smaller than one and is asymptotically stable. The disease-free equilibrium point is unstable when R0>1. We showed that the endemic equilibrium point is unique for R0>1. Also, the most influential control parameters of the spread of malaria were identified. Numerical simulations of both classical and fractional order were conducted, and we used ODE (45) for classical part and numerical technique developed by Toufik and Atangana for fractional order. The infected population will grow because of the high biting frequency of the mosquito and the high likelihood of transmission from the infected mosquito to the susceptible human. R=1.622, which is more than one, indicating that the mosquito vector keeps on growing. This supports the stability of the endemic equilibrium point theorem, which states that the disease becomes endemic when R=1. The susceptible human population will decrease because of the presence of the infective mosquito, which has a high biting frequency for the first couple of days. Since the infective mosquito bit the susceptible human, the susceptible human became infected and went to the infected human compartments. Then, the susceptible population will decrease and the infested human population will increase. After a certain amount of time, it becomes zero due to the growth of protected classes. In this case, a disease-free equilibrium point exists and is stable. This condition exists because R0=2.827×10−5 is less than 1. This supports the theorem that the stability of the disease-free equilibrium point is obtained when R0<1. Depending on equation, we have shown that the possibility of some endemic equilibria exists when R0<1, that is, it undergoes backward bifurcation, even when the disease-free equilibrium is locally stable, and the result means that the society may misunderstand the level of malaria prevalence in the community.

Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model.

Mpox (formerly monkeypox) is an infectious disease that spreads mostly through direct contact with infected animals or people's blood, bodily fluids, or cutaneous or mucosal lesions. In light of the global outbreak that occurred in 2022-2023, in this paper, we analyzed global Mpox univariate time series data and provided a comprehensive analysis of disease outbreaks across the world, including the USA with Brazil and three continents: North America, South America, and Europe. The novelty of this study is that it delved into the Mpox time series data by implementing the data-driven methods and a mathematical model concurrently-an aspect not typically addressed in the existing literature. The study is also important because implementing these models concurrently improved our predictions' reliability for infectious diseases. We proposed a traditional compartmental model and also implemented deep learning models (1D- convolutional neural network (CNN), long-short term memory (LSTM), bidirectional LSTM (BiLSTM), hybrid CNN-LSTM, and CNN-BiLSTM) as well as statistical time series models: autoregressive integrated moving average (ARIMA) and exponential smoothing on the Mpox data. We also employed the least squares method fitting to estimate the essential epidemiological parameters in the proposed deterministic model. The primary finding of the deterministic model is that vaccination rates can flatten the curve of infected dynamics and influence the basic reproduction number. Through the numerical simulations, we determined that increased vaccination among the susceptible human population is crucial to control disease transmission. Moreover, in case of an outbreak, our model showed the potential for epidemic control by adjusting the key epidemiological parameters, namely the baseline contact rate and the proportion of contacts within the human population. Next, we analyzed data-driven models that contribute to a comprehensive understanding of disease dynamics in different locations. Additionally, we trained models to provide short-term (eight-week) predictions across various geographical locations, and all eight models produced reliable results. This study utilized a comprehensive framework to investigate univariate time series data to understand the dynamics of Mpox transmission. The prediction showed that Mpox is in its die-out situation as of July 29, 2023. Moreover, the deterministic model showed the importance of the Mpox vaccination in mitigating the Mpox transmission and highlighted the significance of effectively adjusting key epidemiological parameters during outbreaks, particularly the contact rate in high-risk groups.

Modeling the Transmission Routes of Hepatitis E Virus as a Zoonotic Disease Using Fractional‐Order Derivative

Hepatitis E virus (HEV) is one of the emerging zoonotic diseases in Sub‐Saharan Africa. Domestic pigs are considered to be the main reservoir for this infectious disease. A third of the world’s population is thought to have been exposed to the virus. The zoonotic transmission of the HEV raises serious zoonotic and food safety concerns for the general public. This is a major public health issue in both developed and developing countries. The World Health Organization (WHO) estimated that 44,000 people died in 2015 as a result of HEV infection. East and South Asia have the highest prevalence of this disease overall. In this study, we proposed, developed, and analyzed the transmission routes of the infection using a fractional‐order derivative approach. The existence, stability, and uniqueness of solutions were established using the approach and concept in Banach space. Local and global stability was determined using the Hyers–Ulam (HU) stability approach. Numerical simulation was conducted using existing parameter values, and it was established that, as the susceptible human population declines, the number of infected human populations rises with a change in fractional order . When the susceptible pig population increases, the number of infected pig populations rises with a change in . It was observed that a few variations in the fractional derivative order did not alter the function’s overall behavior with the results of numerical simulations. Moreover, as the number of recovered human populations increases, there is a corresponding increase in the population of recovered pigs with a change in . The exponential increase in the infected pig population can be controlled by treatment of the infected pigs and prevention of the susceptible pigs. The authors recommend policymakers, and stakeholders prioritize the fight against the virus by enforcing the prevention of humans and treatment of infected pigs. The model can be extended to optimal control and cost‐effectiveness analysis to determine the most effective control strategy that comes with less cost in the combat of the disease.

A New Stochastic Model for the Aedes aegypti Life Cycle and the Dengue Virus Transmission

Dengue is a viral infection transmitted mainly by the Aedes aegypti mosquito and to a lesser extent by the Aedes albopictus. This infectious disease generally causes flu-like symptoms, but it can also lead to life-threatening symptoms. Unfortunately, the number of cases increases every year and about a third part of the world’s population is at risk of contracting this disease. To generate tools capable of containing dengue transmission, we present a novel stochastic model for the Aedes aegypti life cycle and the dengue virus transmission, taking into account all the mechanisms of transmission and parameters estimated experimentally to date. This new model describes in detail all the interactions in the stages of the life cycle of the mosquito. It also considers the environmental conditions, i.e., the breeding sites and the temperature, which are very important factors for the mosquito survival. The results show that the contagion by bite only does not provoke an epidemic outbreak when five infected, pregnant, and fed females, looking for lay eggs, arrive to a susceptible human population. However, if in addition to the bite transmission, the virus is also transmitted in vertical transmission and sexual ways, then an outbreak arises. Altogether, the transmission mechanisms and the adequate environmental conditions could explain the virus persistence in the population. Under these conditions and by considering fumigation as a way to control the mosquito population, in this new model the outbreak and the virus propagation could be avoided—but only if the control is implemented within the first two weeks of the presence of the virus.

Optimal control on education, vaccination, and treatment in the model of dengue hemorrhagic fever

Dengue hemorrhagic fever (DHF) is an infection caused by the dengue virus which is transmitted by the Aedes aegypti mosquito. In this paper, a model of the spread of dengue disease is developed using optimal control theory by dividing the population into Susceptible, Exposed, Infected, and Recovered (SEIR) sub-populations. The Pontryagin minimum principle of the fourth-order Runge-Kutta method is used in the model of the spread of dengue disease by incorporating control factors in the form of education and vaccination of susceptible human populations, as well as treatment of infected human populations. Optimum control aims to minimize the infected human population in order to reduce the spread of DHF. Simulations were carried out for two cases, namely when the basic reproduction number is less than one for disease-free conditions and greater than one for endemic conditions. Based on numerical simulations of the SEIR epidemic model with controls, it results that the optimal strategy is achieved if education controls, vaccinations, and medication are used.

Mercury Exposure in Two Fish Trophic Guilds from Protected and ASGM-Impacted Reservoirs in Zimbabwe and Possible Risks to Human Health

Despite a surge in mercury (Hg) pollution from artisanal and small-scale gold mining (ASGM) in Zimbabwe's drainage basins, little is known about Hg trophodynamics in the country's major reservoirs. We analyzed fish tissues for total mercury (THg) and stable isotopes of nitrogen and carbon (δ15N and δ13C) to compare patterns of biomagnification between two trophic guilds from a protected reservoir (Chivero) and an ASGM-impacted reservoir (Mazowe) and assessed consequences for human and fish health. Mean dry weight THg concentrations were significantly higher for both piscivorous and herbivorous fishes from Mazowe reservoir compared to fishes from similar feeding guilds in Chivero. Trophic magnification slopes (TMS), inferred from linear regressions between log10[THg] and δ15N, revealed significant Hg biomagnification in Mazowe (TMS = 0.28; p < 0.05) and no evidence for Hg biomagnification in Chivero (TMS = -0.005; p > 0.05). In Mazowe's piscivorous fishes, 32% had wet weight THg concentrations that surpassed 0.2µg/g ww, a threshold for susceptible human populations and biochemical and gene expression alterations in fish. In addition, 17% of Mazowe's piscivorous fishes surpassed the UNEP THg toxicity threshold for human consumption (0.5µg/g ww). To reduce exposure to Hg toxicity in humans, the maximum fish consumption for piscivorous species from Mazowe reservoir should not exceed 431g/week for both adult male and female consumers. Our findings demonstrate the importance of creating freshwater-protected areas to prevent direct Hg contamination of aquatic ecosystems and the need for health agencies to provide fish consumption advisories to vulnerable communities.

Modeling the variable transmission rate and various discharges on the spread of Malaria

&lt;abstract&gt;&lt;p&gt;Natural and household discharges are the natural breeding grounds of various mosquito species, including female &lt;italic&gt;Anopheles&lt;/italic&gt; mosquitoes, which transmit the &lt;italic&gt;Plasmodium&lt;/italic&gt; parasite, causing the spread of the life-threatening disease malaria. Apart from that, population migrations also have a substantial impact on malaria transmission, claiming about half a million lives every year around the world. To assess the effects of the cumulative density of households and other natural discharges, and emigration-dependent interaction rates on the dissemination of the vector-borne infectious disease malaria, we propose and analyze a non-linear mathematical model. The model comprises five dependent variables, namely, the density of the susceptible human population, the density of the infective human population, the density of the susceptible female &lt;italic&gt;Anopheles&lt;/italic&gt; mosquito population, the density of the infective mosquito population and cumulative density of household and other natural discharges. In the model, the density of the mosquito population is supposed to follow logistic growth, whose intrinsic growth rate is a linear function of the cumulative density of household and other natural discharges. The nonlinear model is analyzed by using the stability theory of differential equations, numerical simulations and sensitivity analysis. The analysis shows that an increase in non-emigrating population causes increased incidence of malaria. It is also found that an increase in household and other natural discharges accelerates the occurrence of malaria. A basic differential sensitivity analysis is carried out to assess the sensitivity of model solutions with respect to key parameters. The model's numerical simulations demonstrate the analytical findings.&lt;/p&gt;&lt;/abstract&gt;

Copro-ELISA-based prevalence and risk determinants of giardiasis in cattle and sheep populations raised by socio-economically deprived urban nomadic communities located in and around Multan, Punjab-Pakistan

ABSTRACT This study reports the copro-prevalence of giardiasis in sheep and cattle populations of nomadic communities in Multan-Pakistan. For this purpose, a total of 184 faecal samples were collected from cattle (n = 92) and sheep (n = 92) raised by the nomads. All samples were analyzed by using species-specific ELISA kits for the detection of copro-antigen of Giardia duodenalis. Results showed that the overall prevalence of giardiasis was 21.20%, whereas, in sheep and cattle, the prevalence rates were 19.18% and 23.91%, respectively. Age, clinico-physical status and drinking water source showed significant association (P < 0.05) with giardiasis in both sheep and cattle. Breed, history of gastrointestinal problems and routine vaccination were also significant (P < 0.05) risk factors in sheep but not in cattle. Deworming history had a significant association (P < 0.05) with giardiasis in cattle population only. Conversely, sex, herd size, farmers’ educational status, feeding pattern, physiological status, contact with wildlife and Giardia-susceptible animals and hygienic condition of housing facility showed non-significant association (P > 0.05) with giardiasis. In conclusion, the cattle and sheep raised by the nomads are infected with giardiasis and may pose a serious threat to susceptible animal and human populations in their surrounding regions.

Recent review of COVID-19 management: diagnosis, treatment and vaccination.

The idiopathic Coronavirus disease 2019 (COVID-19) pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached global proportions; the World Health Organization (WHO) declared it as a public health emergency during the month of January 30, 2020. The major causes of the rise of new variants of SARS-CoV-2 are genetic mutations and recombination. Some of the variants with high infection and transmission rates are termed as variants of concern (VOCs) like currently Omicron variants. Pregnant women, aged people, and immunosuppressed and compromised patients constitute the most susceptible human population to the SARS-CoV-2 infection, especially to the new evolving VOCs. To effectively manage the pathological condition of infection, the focus should be directed towards prevention and prophylactic approach. In this narrative review, we aimed to analyze the current scenario of COVID-19 management and discuss the treatment and prevention strategies. We also focused on the complications prevalent during the COVID-19 and post-COVID period and to discuss the novel approaches developed for mitigation of the global pandemic. We have also emphasized on the COVID-19 management approaches for the special population including children, pregnant women, aged groups, and immunocompromised patients. We conclude that the advancements in therapeutic and pharmacological domains have provided opportunities to develop and design novel diagnosis, treatment, and prevention strategies. New advanced techniques such as RT-LAMP, RT-qPCR, High-Resolution Computed Tomography, etc., efficiently diagnose patients with SARS-CoV-2 infection. In the case of treatment options, new drugs like paxlovid, combinations of β-lactum drugs and molnupiravir are found to be effective against even the new emerging variants. In addition, vaccination is an essential approach to prevent the infection or to reduce its severity. Vaccines for against COVID-19 from Comirnaty by Pfizer-BioNTech, SpikeVax by Moderna, and Vaxzevria by Oxford-AstraZeneca are approved and used widely. Similarly, numerous vaccines have been developed with different percentages of effectiveness against VOCs. New developments like nanotechnology and AI can be beneficial in providing an efficient and reliable solution for the suppression of SARS-CoV-2. Public health concerns can be efficiently treated by a unified scientific approach, public engagement, and better diagnosis.

Evolving dynamics of Aedes-borne diseases in Africa: a cause for concern.

Aedes-borne viruses, yellow fever (YF), dengue, Chikungunya and Zika are taking a huge toll on global health as Africa faces re-emergence with potential for massive human catastrophe. Transmission driven by diverse vectors in ecological settings that range from urban to rural and sylvatic habitats with human and nonhuman primate/reservoir activities across such habitats hasfacilitated virus movement and spillover to susceptible human populations. Approved vaccine exists for YF, although availability for routine and mass vaccination is often constrained. Integrating vector surveillance, understanding disease ecology with rationalised vaccination in high-risk areas (YF) remains important in disease prevention and control. We review trends in disease occurrence in Africa, hinting on gaps in disease detection and management and the prospects for prevention and/or control.

Model Epidemi Suspected Exposed Infected Recovered (SEIR) Pada Penyebaran COVID-19 Orde-Fraksional

This article discusses the solution to the fractional order SEIR equation with the help of the Homotopy Perturbation Method (HPM). This mathematical model is the SEIR model of the spread of COVID-19 cases in Indonesia. In general, the nonlinear Ordinary Differential Equation System (ODES) solution is quite difficult to solve analytically, so this research will transform the nonlinear ODES into a Fractional Differential Equation System (FDES). The method used in completing this research is the HPM method. The solution for the fractional order by the HPM method is obtained by the following steps: 1). Multiply each SEIR equation against the embedding parameter and equate each coefficient in the assumed infinite series to find the solution, 2). Simulate numerical solutions and perform graph interpretation. The numerical simulation shows that the susceptible human population, the infected human population without symptoms, the recovered human population has increased, in contrast to the infected human population with decreased symptoms. The HPM method in its numerical solution shows a fairly small comparison to the nonlinear ODES solution.

Impact of Hygiene on Malaria Transmission Dynamics: A Mathematical Model

Malaria continues to pose a major public health challenge, especially in developing countries, as 219 million cases of malaria were found in 89 countries. In this paper, a mathematical model using non-linear differential equations is formulated to describe the impact of hygiene on malaria transmission dynamics. The model is divided into seven compartments which includes five human compartments namely; unhygienic susceptible human population (Su), hygienic susceptible human population (Sn), unhygienic infected human population (Iu), hygienic infected human population (In) and the recovered human population (Rn) while the mosquito population is subdivided into susceptible mosquitoes (Sv) and infected mosquitoes Iv. The positivity of the solution shows that a domain exists where the model is biologically meaningful and mathematically well-posed. The Disease-Free Equilibrium (DFE) point of the model is obtained. Then, the basic reproduction number is computed using the next generation method and established the condition for local stability of the disease-free equilibrium. Thereafter the global stability of the disease-free equilibrium was obtained by constructing the Lyapunov function of the model system. Also, sensitivity analysis of the model system was carried out to identify the influence of the parameters on the basic reproduction number. The result shows that the natural death rate of the mosquitoes is most sensitive to the basic reproduction number.

Modelling the Role of Treatment, Public Health Education, and Chemical Control Strategies on Transmission Dynamics of Schistosomiasis

In this study, a mathematical model for the transmission dynamics and control of schistosomiasis is studied using a system of nonlinear ordinary differential equations. The basic reproduction number ℛ0 for the model is obtained, and its dependence on model parameters is discussed. Analytical results reveal that the disease‐free equilibrium point is globally stable if and only if the basic reproduction number ℛ0 &lt; 1, indicating that the disease would be wiped out of the community, and the endemic equilibrium point is globally stable if ℛ0 &gt; 1 and the disease would persist at the endemic steady state. Numerical simulations reveal that a combination of treatment, public health education, and chemical control intervention strategies significantly increased the number of susceptible human population and susceptible snail population while significantly decreasing the number of infected humans, miracidia, infected snails, and cercariae. The results further indicate that a combination of treatment, public health education, and chemical control intervention strategies can effectively manage the transmission of schistosomiasis in endemic areas.

Optimal Control and Stability Analysis of Malaria disease: A model Based Approach

In this paper we have proposed a three dimensional mathematical model on malaria disease by considering two distinct classes namely susceptible and infected human population and infected mosquito population. Basic reproductive number of the system has been obtained and its relation regarding the behavior of the system has been established. Two control parameters, namely treatment control on infected human population and insecticide control on mosquito populations are applied in the present system. We formulate and solve the optimal control problem considering treatment and insecticide as the control variables. All the theoretical results are verified by some computer simulation works.

The impact of time delay in the transmission of Japanese encephalitis without vaccination

In this manuscript, the influence of time delay in the transmission of Japanese encephalitis without vaccination model has been studied. The time delay is because of the existence of an incubation period during which the Japanese encephalitis virus reproduces enough in the mosquitoes with the goal that it tends to be transmitted by the mosquitoes to people. The motivation behind this manuscript is to assess the influence of the time delay it takes to infect susceptible human populations after interacting with infected mosquitoes. The steadystate and the threshold value R0 of the delay model were resolved. This value assists with setting up the circumstance that ensures the asymptotic stability of relating equilibrium points. Utilizing the delay as a bifurcation parameter, we built up the circumstance for the presence of a Hopf bifurcation. Moreover, we infer an express equation to decide the stability and direction of Hopf bifurcation at endemic equilibrium by using center manifold theory and normal structure strategy. It has been seen that delay plays a vital role in stability exchanging. Furthermore, the presence of Hopf bifurcation is affected by larger values of virus transmission rate from an infected mosquito to susceptible individuals and the natural mortality of humans in a model. Finally, to understand some analytical outcomes, the delay framework is simulated numerically.

QUASISPECIES FEATURE IN SARS-CoV-2

Since the identification of the SARS-CoV-2, genus Beta- Coronavirus, in January 2020, the virus quickly spread in less than 3 months to all continents with a susceptible human population of about a 7.9billion, and still in active circulation. In the process, it has accumulated mutations leading to genetic diversity. Regular emergence of variants of concern/significance in different ecology shows genetic heterogeneity in the base population of SARS-CoV-2 that is continuously expanding with the passage of the virus in the vast susceptible human population. Natural selection of mutant occurs frequently in a positive sense (+) single-stranded (ss) RNA virus upon replication in the host. The Pressure of sub-optimal levels of virus-neutralizing antibodies and also innate immunity influence the process of genetic/ antigenic selection. The fittest of the mutants, that could be more than one, propagate and emerge as variants. The existence of different lineages, clades, and strains, as well as genetic heterogeneity of plaque purified virus population, justifies SARS-CoV-2 as ‘Quasispecies’ that refers to swarms of mutant sequences generated during replication of the viral genome, and all mutant sequences may not lead to virion. Viruses having a quasispecies nature may end up with progressive antigenic changes leading to antigenic plurality that is driven by ecology, and this phenomenon challenges vaccination-based control programs.