Paleoepidemiological Considerations of Mobility and Population Interaction in the Spread of Infectious Diseases in the Prehistoric Past

2021 ◽  
Author(s):  
Melandri Vlok ◽  
Hallie Buckley
Keyword(s):  
Infectious Disease ◽  
Population Density ◽  
Infectious Diseases ◽  
Residential Mobility ◽  
Human Interaction ◽  
Disease Spread ◽  
Relative Risk Ratio ◽  
Disease Patterns ◽  
Population Interaction ◽  
The Impact

The processes of human mobility have been well demonstrated to influence the spread of infectious disease globally in the present and the past. However, to date, paleoepidemiological research has focused more on factors of residential mobility and population density as drivers for epidemiological shifts in prehistoric infectious disease patterns. A strong body of epidemiological literature exists for the dynamics of infectious disease spread through networks of mobility and interaction. We review the epidemiological theory of infectious disease spread and propose frameworks for application of this theory to bioarchaeology. We outline problems with current definitions of prehistoric mobility and propose a framework shift with focus on population interactions as nodes for disease transmission. To conceptualize this new framework, we produced a theoretical model that considers the interplay between climate suitability, population density, residential mobility, and human interaction levels to influence infectious disease patterns in prehistoric assemblages. We then tested observable effects of this model in paleoepidemiological data from Asia (n = 343). Relative risk ratio analysis and correlations were used to test the impact of population interaction, residential mobility, population density, climate, and subsistence on the prevalence and diversity of infectious diseases. Our statistical results showed higher levels of population interaction led to significantly higher prevalence of infectious disease in sedentary populations and a significant increase in pathogen diversity in mobile populations. We recommend that population interaction be included as an important component of infectious disease analysis of prehistoric population health alongside other biosocial factors, such as sedentism and population density.   Daar is goed gedemonstreer dat die prosesse van menslike mobiliteit die verspreiding van aansteeklike siektes wêreldwyd in die hede en in die verlede beïnvloed. Maar tot op hede het paleo-epidemiologiese navorsing egter meer gefokus op faktore van residensiële mobiliteit en bevolkingsdigtheid as dryfvere vir epidemiologiese verskuiwings in die prehistoriese infeksiesiektepatrone. Sterk epidemiologiese literatuur bestaan vir die dinamika van aansteeklike siektes wat versprei word deur netwerke van mobiliteit en interaksie. Ons ondersoek die epidemiologiese teorie van die verspreiding van aansteeklike siektes en stel raamwerke voor vir die toepassing van hierdie teorie op die bio-argeologie. Ons skets probleme met huidige definisies van prehistoriese mobiliteit en stel ‘n raamwerk verskuiwing voor met die fokus op bevolkings-interaksies as nodusse vir oordrag van siektes. Om hierdie nuwe raamwerk te konseptualiseer, het ons ‘n teoretiese model vervaardig wat die wisselwerking tussen klimaatsgeskiktheid, bevolkingsdigtheid, residensiële mobiliteit en menslike interaksievlakke oorweeg om die infeksiesiektepatrone in prehistoriese samestellings te beïnvloed. Daarna het ons die waarneembare effekte van hierdie model getoets in paleo-epidemiologiese data uit Asië (n = 343). Relatiewe risiko-verhoudingsanalise en korrelasies is gebruik om die impak van bevolkings-interaksie, residensiële mobiliteit, bevolkingsdigtheid, klimaat en bestaan op die voorkoms en diversiteit van aansteeklike siektes te toets. Ons statistiese resultate het gedemonstreer dat hoër vlakke van bevolkings-interaksie gelei het tot aansienlik hoër voorkoms van aansteeklike siektes in sittende bevolkings en ‘n beduidende toename in patogeen diversiteit in mobiele bevolkings. Ons beveel aan dat bevolkings-interaksie ingesluit word as ‘n belangrike komponent van die aantstekingsiekte-ontleding van die prehistoriese bevolkingsgesondheid, tesame met ander biososiale faktore soos sedentisme en bevolkingsdigtheid.

Paleoepidemiological Considerations of Mobility and Population Interaction in the Spread of Infectious Diseases in the Prehistoric Past

2021 ◽  
Author(s):  
Melandri Vlok ◽  
Hallie Buckley
Keyword(s):  
Infectious Disease ◽  
Population Density ◽  
Infectious Diseases ◽  
Residential Mobility ◽  
Human Interaction ◽  
Disease Spread ◽  
Relative Risk Ratio ◽  
Disease Patterns ◽  
Population Interaction ◽  
The Impact

The processes of human mobility have been well demonstrated to influence the spread of infectious disease globally in the present and the past. However, to date, paleoepidemiological research has focused more on factors of residential mobility and population density as drivers for epidemiological shifts in prehistoric infectious disease patterns. A strong body of epidemiological literature exists for the dynamics of infectious disease spread through networks of mobility and interaction. We review the epidemiological theory of infectious disease spread and propose frameworks for application of this theory to bioarchaeology. We outline problems with current definitions of prehistoric mobility and propose a framework shift with focus on population interactions as nodes for disease transmission. To conceptualize this new framework, we produced a theoretical model that considers the interplay between climate suitability, population density, residential mobility, and human interaction levels to influence infectious disease patterns in prehistoric assemblages. We then tested observable effects of this model in paleoepidemiological data from Asia (n = 343). Relative risk ratio analysis and correlations were used to test the impact of population interaction, residential mobility, population density, climate, and subsistence on the prevalence and diversity of infectious diseases. Our statistical results showed higher levels of population interaction led to significantly higher prevalence of infectious disease in sedentary populations and a significant increase in pathogen diversity in mobile populations. We recommend that population interaction be included as an important component of infectious disease analysis of prehistoric population health alongside other biosocial factors, such as sedentism and population density.   Daar is goed gedemonstreer dat die prosesse van menslike mobiliteit die verspreiding van aansteeklike siektes wêreldwyd in die hede en in die verlede beïnvloed. Maar tot op hede het paleo-epidemiologiese navorsing egter meer gefokus op faktore van residensiële mobiliteit en bevolkingsdigtheid as dryfvere vir epidemiologiese verskuiwings in die prehistoriese infeksiesiektepatrone. Sterk epidemiologiese literatuur bestaan vir die dinamika van aansteeklike siektes wat versprei word deur netwerke van mobiliteit en interaksie. Ons ondersoek die epidemiologiese teorie van die verspreiding van aansteeklike siektes en stel raamwerke voor vir die toepassing van hierdie teorie op die bioargeologie. Ons skets probleme met huidige definisies van prehistoriese mobiliteit en stel ‘n raamwerk verskuiwing voor met die fokus op bevolkings-interaksies as nodusse vir oordrag van siektes. Om hierdie nuwe raamwerk te konseptualiseer, het ons ‘n teoretiese model vervaardig wat die wisselwerking tussen klimaatsgeskiktheid, bevolkingsdigtheid, residensiële mobiliteit en menslike interaksievlakke oorweeg om die infeksiesiektepatrone in prehistoriese samestellings te beïnvloed. Daarna het ons die waarneembare effekte van hierdie model getoets in paleo-epidemiologiese data uit Asië (n = 343). Relatiewe risiko-verhoudingsanalise en korrelasies is gebruik om die impak van bevolkings-interaksie, residensiële mobiliteit, bevolkingsdigtheid, klimaat en bestaan op die voorkoms en diversiteit van aansteeklike siektes te toets. Ons statistiese resultate het gedemonstreer dat hoër vlakke van bevolkings-interaksie gelei het tot aansienlik hoër voorkoms van aansteeklike siektes in sittende bevolkings en ‘n beduidende toename in patogeen diversiteit in mobiele bevolkings. Ons beveel aan dat bevolkings-interaksie ingesluit word as ‘n belangrike komponent van die aantstekingsiekte-ontleding van die prehistoriese bevolkingsgesondheid, tesame met ander biososiale faktore soos sedentisme en bevolkingsdigtheid.

scholarly journals The Influence of War and Conflict on Infectious Disease: A Rapid Review of Historical Lessons We Have Yet to Learn

2021 ◽  
Vol 13 (19) ◽  
pp. 10783
Author(s):  
Krzysztof Goniewicz ◽  
Frederick M. Burkle ◽  
Simon Horne ◽  
Marta Borowska-Stefańska ◽  
Szymon Wiśniewski ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Low Income ◽  
Respiratory Infections ◽  
Communicable Disease ◽  
Armed Conflicts ◽  
Disease Spread ◽  
Low Income Countries ◽  
Rapid Review ◽  
The Impact

Armed conflicts degrade established healthcare systems, which typically manifests as a resurgence of preventable infectious diseases. While 70% of deaths globally are now from non-communicable disease; in low-income countries, respiratory infections, diarrheal illness, malaria, tuberculosis, and HIV/AIDs are all in the top 10 causes of death. The burden of these infectious diseases is exacerbated by armed conflict, translating into even more dramatic long-term consequences. This rapid evidence review searched electronic databases in PubMed, Scopus, and Web of Science. Of 381 identified publications, 73 were included in this review. Several authors indicate that the impact of infectious diseases increases in wars and armed conflicts due to disruption to surveillance and response systems that were often poorly developed to begin with. Although the true impact of conflict on infectious disease spread is not known and requires further research, the link between them is indisputable. Current decision-making management systems are insufficient and only pass the baton to the next unwary generation.

Everyday Dangers – The Impact Infectious Disease has on the Health of Paramedics: A Scoping Review

2017 ◽  
Vol 32 (2) ◽  
pp. 217-223 ◽  
Author(s):  
Brodie Thomas ◽  
Peter O’Meara ◽  
Evelien Spelten
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Scoping Review ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Publication Type ◽  
Knowledge And Attitudes ◽  
Immunodeficiency Virus ◽  
Potential Risks ◽  
The Impact ◽  
Mrsa Colonization

AbstractBackgroundParamedics respond to emergency scenes in often uncontrolled settings without being aware of potential risks. This makes paramedicine one of the most dangerous occupations. One of these dangers is the risk of contracting infectious diseases. Research in this area is predominantly focused on compliance in the use of protective equipment, attitudes and perceptions of paramedics, infectious disease policy, and exposure rates to blood and body fluids. The purpose of this scoping review was to determine what is known about the impact of infectious disease on the health of paramedics.MethodsUsing the Arskey and O’Malley methodological framework, a scoping review was undertaken, which allows for a broad search of the available evidence.ResultsThe literature search identified eight articles for review that reported on paramedic exposure trends; the lack of reported blood-borne infections contracted, such as hepatitis B, hepatitis C, and human immunodeficiency virus (HIV); instances of severe acute respiratory syndrome (SARS) infections; and the higher prevalence of methicillin-resistant staphylococcus aureus (MRSA) nasal infections amongst paramedics.ConclusionsExposure to infectious diseases is decreasing, yet it remains significant. The decrease is attributed to prevention strategies; however, paramedic knowledge and attitudes as well as the uncontrolled environment paramedics work in can be a barrier. Contraction of infectious diseases is generally low; exceptions to this are MRSA colonization, influenza, and SARS. Paramedics are at greater risk of acquiring these infectious diseases compared to the general public. The effect on the health of paramedics is not well reported.ThomasB,O’MearaP,SpeltenE.Everyday dangers – the impact infectious disease has on the health of paramedics: a scoping review.Prehosp Disaster Med.2017;32(2):217–223.

Telephone Calls to an Infectious Diseases Fellow

PEDIATRICS ◽  
1995 ◽  
Vol 95 (5) ◽  
pp. 753-754
Author(s):  
Mark F. Cotton
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Time Allocation ◽  
Primary Care Physicians ◽  
First Year ◽  
Educational Value ◽  
The Mean ◽  
Telephone Calls ◽  
The Impact ◽  
Mean Time

Objective. There is no information on the impact and nature of telephone calls directed to subspecialists. The main objective was to document prospectively all calls directed to a first-year infectious diseases fellow, to determine their content, origin, educational value, and time allocation. Results. Three hundred fifty-nine calls were received over a 71-day period from March 24 through May 20, 1992. The mean number of daily calls was 5.1 ± 3.3. Mean time per call was 7 ± 5.4 minutes. Cumulatively, 41.7 hours were spent responding to telephone calls. The subgroup with the most calls (44.3%) was from pediatricians in practice. Seventy percent of calls were for advice about case management. Forty percent of calls were considered educational to the fellow. Conclusions. This study confirms the importance of the infectious disease subspecialist as a resource for primary care physicians.

8. Looking ahead

2015 ◽  
pp. 97-106
Author(s):  
Marta L. Wayne ◽  
Benjamin M. Bolker
Keyword(s):  
Infectious Disease ◽  
Disease Management ◽  
Infectious Diseases ◽  
Disease Ecology ◽  
Control Strategies ◽  
Zoonotic Diseases ◽  
Transmission Control ◽  
Living Things ◽  
Life Itself ◽  
The Impact

‘Looking ahead’ shows how our understanding of disease ecology and evolution has revolutionized disease management. By developing transmission control strategies to close the encounter filter and vaccines and treatments to close the compatibility filter, we have reduced the misery caused by infectious disease. But what is the outlook for the future control of infectious diseases? We cannot eradicate infectious disease. Living things have parasitized one another since the beginning of life itself. New zoonotic diseases will continue to emerge, and existing diseases will continually evolve to escape our methods of control. Despite this stark reality, we can minimize the impact of disease even if we can never fully conquer it.

scholarly journals The bibliometric landscape of infectious disease research in Panama (1990 - 2019): An evaluation of the country’s capability on One Health

2020 ◽  
Author(s):  
Jose Loaiza ◽  
Robinson Zapata ◽  
Rao Kosagisharaf ◽  
Rolando A. Gittens ◽  
Enrique Mendoza ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
One Health ◽  
Scientific Publications ◽  
Strategic Investment ◽  
Disease Research ◽  
Infectious Disease Research ◽  
Health Related ◽  
Number Of Publications ◽  
The Impact

Abstract Background: This work aims to analyze the landscape of scientific publications on subjects related to One Health and infectious diseases in Panama. Methods: Boolean searches on the Web of Science, SCOPUS and PubMed were undertaken to evaluate the main trends of publications related to One Health and infectious disease research in the country of Panama, between 1990 and 2019. Results: 4,547 publications were identified since 1990, including 3,564 peer-reviewed articles interconnected with One Health related descriptors, and 211 articles focused particularly on infectious diseases. There was a pattern of exponential growth in the number of publications with various contributions from Panamanian institutions. The rates of multidisciplinary, inter-institutional and inter-sectoral research ranged from moderate to low, to very low, respectively. Research efforts have centered largely on protozoan, neglected and arthropod-borne diseases with a strong emphasis on malaria, Chagas and leishmaniasis. Conclusion: Panama has scientific capabilities on One Health to tackle future infectious disease threats, but the official collaboration schemes and strategic investment to develop further competencies need to be considered. Through future collaborative efforts, Panama can reduce the risk of pandemics by developing surveillance strategies to improve the prediction of disease spillover, spread and persistence while helping to mitigate the impact on public health and the economy, regionally.

scholarly journals Data-Driven Computational Model to Assess the Risk of Epidemics in Global Mass Gatherings

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Sultanah Alshammari ◽  
Armin Mikler
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Computational Models ◽  
Disease Spread ◽  
Agent Based Model ◽  
Agent Based ◽  
Mass Gatherings ◽  
Proposed Model ◽  
Health Related ◽  
The Impact

ObjectiveTo develop a computational model to assess the risk of epidemics in global mass gatherings and evaluate the impact of various measures of prevention and control of infectious diseases.IntroductionGlobal Mass gatherings (MGs) such as Olympic Games, FIFA World Cup, and Hajj (Muslim pilgrimage to Makkah), attract millions of people from different countries. The gathering of a large population in a proximity facilitates transmission of infectious diseases [1]. Attendees arrive from different geographical areas with diverse disease history and immune responses. The associated travel patterns with global events can contribute to a further disease spread affecting a large number of people within a short period and lead to a potential pandemic. Global MGs pose serious health threats and challenges to the hosting countries and home countries of the participants [2]. Advanced planning and disease surveillance systems are required to control health risks in these events. The success of computational models in different areas of public health and epidemiology motivates using these models in MGs to study transmission of infectious diseases and assess the risk of epidemics. Computational models enable simulation and analysis of different disease transmission scenarios in global MGs. Epidemic models can be used to evaluate the impact of various measures of prevention and control of infectious diseases.MethodsThe annual event of the Hajj is selected to illustrate the main aspects of the proposed model and to address the associated challenges. Every year, more than two million pilgrims from over 186 countries arrive in Makkah to perform Hajj with the majority arriving by air. Foreign pilgrims can stay at one of the holy cities of Makkah and Madinah up to 30-35 days prior the starting date of the Hajj. The long duration of the arrival phase of the Hajj allows a potential epidemic to proceed in the population of international pilgrims. Stochastic SEIR (Susceptible−Exposed−Infected−Recovered) agent-based model is developed to simulate the disease transmission among pilgrims. The agent-based model is used to simulate pilgrims and their interactions during the various phases of the Hajj. Each agent represents a pilgrim and maintains a record of demographic data (gender, country of origin, age), health data (infectivity, susceptibility, number of days being exposed or infected), event related data (location, arrival date and time), and precautionary or health-related behaviors.Each pilgrim can be either healthy but susceptible to a disease, exposed who are infected but cannot transmit the infection, or infectious (asymptomatic or symptomatic) who are infected and can transmit the disease to other susceptibles. Exposed individuals transfer to the infectious compartment after 1/α days, and infectious individuals will recover and gain immunity to that disease after 1/γ days. Where α is the latent period and γ is the infectious period. Moving susceptible individuals to exposed compartment depends on a successful disease transmission given a contact with an infectious individual. The disease transmission rate is determined by the contact rate and thetransmission probability per contact. Contact rate and mixing patterns are defined by probabilistic weights based on the features of infectious pilgrims and the duration and setting of the stage where contacts are taking place. The initial infections are seeded in the population using two scenarios (Figure 1) to measure the effects of changing, the timing for introducing a disease into the population and the likelihood that a particular flight will arrive with one or more infected individuals.ResultsThe results showed that the number of initial infections is influenced by increasing the value of λ and selecting starting date within peak arrival days. When starting from the first day, the average size of the initial infectious ranges from 0.05% to 1% of the total arriving pilgrims. Using the SEIR agent-based model, a simulation of the H1N1 Influenza epidemic was completed for the 35-days arrival stage of the Hajj. The epidemic is initiated with one infectious pilgrim per flight resulting in infected 0.5% of the total arriving pilgrims. As pilgrims spend few hours at the airport, the results obtained from running the epidemic model showed only new cases of susceptible individuals entering the exposed state in a range of 0.20% to 0.35% of total susceptibles. The number of new cases is reduced by almost the same rate of the number of infectious individuals following precautionary behaviors.ConclusionsA data-driven stochastic SEIR agent-based model is developed to simulate disease spread at global mass gatherings. The proposed model can provide initial indicators of infectious disease epidemic at these events and evaluate the possible effects of intervention measures and health-related behaviors. The proposed model can be generalized to model the spread of various diseases in different mass gatherings, as it allows different factors to vary and entered as parameters.References1. Memish ZA, Stephens GM, Steffen R, Ahmed QA. Emergence of medicine for mass gatherings: lessons from the Hajj. The Lancet infectious diseases. 2012 Jan 31;12(1):56-65.2. Chowell G, Nishiura H, Viboud C. Modeling rapidly disseminating infectious disease during mass gatherings. BMC medicine. 2012 Dec 7;10(1):159.

scholarly journals The Bibliometric Landscape of Infectious Disease Research in Panama (1990 - 2019): An Evaluation of the Country’s Capability on One Health

2020 ◽  
Author(s):  
Jose Loaiza ◽  
Robinson Zapata ◽  
Rao Kosagisharaf ◽  
Rolando A. Gittens ◽  
Enrique Mendoza ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
One Health ◽  
Scientific Publications ◽  
Disease Research ◽  
Infectious Disease Research ◽  
Health Concept ◽  
Health Related ◽  
The One ◽  
The Impact

Abstract Background: This work aims to analyze the landscape of scientific publications on subjects related to One Health and infectious diseases in Panama. We asked the following specific questions: How does the One Health research landscape look like in Panama? Are historical research efforts aligned with the One Health concept? What infectious diseases have received more attention from the local scientific community since 1990?Methods: Boolean searches on the Web of Science, SCOPUS and PubMed were undertaken to evaluate the main trends of publications related to One Health and infectious disease research in the country of Panama, between 1990 and 2019. Results: 4,547 publications were identified since 1990, including 3,564 peer-reviewed articles interconnected with One Health related descriptors, and 211 articles focused particularly on infectious diseases. There was a pattern of exponential growth in the number of publications with various contributions from Panamanian institutions. The rates of multidisciplinary, inter-institutional and inter-sectoral research ranged from moderate to low, to very low, respectively. Research efforts have centered largely on protozoan, neglected and arthropod-borne diseases with a strong emphasis on malaria, Chagas and leishmaniasis. Conclusion: Panama has scientific capabilities on One Health to tackle future infectious disease threats, but the official collaboration schemes and strategic investment to develop further competencies need to be considered. Through future collaborative efforts, Panama can reduce the risk of pandemics by developing surveillance strategies to improve the prediction of disease spillover, spread and persistence while helping to mitigate the impact on public health and the economy, regionally.

scholarly journals Incubation periods impact the spatial predictability of outbreaks: analysis of cholera and Ebola outbreaks in Sierra Leone

2019 ◽  
Author(s):  
Rebecca Kahn ◽  
Corey M. Peak ◽  
Juan Fernández-Gracia ◽  
Alexandra Hill ◽  
Amara Jambai ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Sierra Leone ◽  
Incubation Period ◽  
Population Connectivity ◽  
Disease Spread ◽  
Long Distance ◽  
Spatial Spread ◽  
Transmission Parameters ◽  
Incubation Periods ◽  
The Impact

AbstractForecasting the spatiotemporal spread of infectious diseases during an outbreak is an important component of epidemic response. However, it remains challenging both methodologically and with respect to data requirements as disease spread is influenced by numerous factors, including the pathogen’s underlying transmission parameters and epidemiological dynamics, social networks and population connectivity, and environmental conditions. Here, using data from Sierra Leone we analyze the spatiotemporal dynamics of recent cholera and Ebola outbreaks and compare and contrast the spread of these two pathogens in the same population. We develop a simulation model of the spatial spread of an epidemic in order to examine the impact of a pathogen’s incubation period on the dynamics of spread and the predictability of outbreaks. We find that differences in the incubation period alone can determine the limits of predictability for diseases with different natural history, both empirically and in our simulations. Our results show that diseases with longer incubation periods, such as Ebola, where infected individuals can travel further before becoming infectious, result in more long-distance sparking events and less predictable disease trajectories, as compared to the more predictable wave-like spread of diseases with shorter incubation periods, such as cholera.Significance statementUnderstanding how infectious diseases spread is critical for preventing and containing outbreaks. While advances have been made in forecasting epidemics, much is still unknown. Here we show that the incubation period – the time between exposure to a pathogen and onset of symptoms – is an important factor in predicting spatiotemporal spread of disease and provides one explanation for the different trajectories of the recent Ebola and cholera outbreaks in Sierra Leone. We find that outbreaks of pathogens with longer incubation periods, such as Ebola, tend to have less predictable spread, whereas pathogens with shorter incubation periods, such as cholera, spread in a more predictable, wavelike pattern. These findings have implications for the scale and timing of reactive interventions, such as vaccination campaigns.

scholarly journals An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India

2020 ◽  
Author(s):  
Ashutosh Mahajan ◽  
Ravi Solanki ◽  
Namitha Sivadas
Keyword(s):  
High Risk ◽  
Population Density ◽  
Epidemic Model ◽  
Disease Spread ◽  
High Population ◽  
High Population Density ◽  
Social Distancing ◽  
Rapid Pace ◽  
The Impact ◽  
Death Cases

AbstractAfter originating from Wuhan, China, in late 2019, with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread.

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