Lockdowns to Contain COVID-19 Increase Risk and Severity of Mosquito-Borne Disease Outbreaks

Disease Outbreaks ◽

Communicable Diseases ◽

Intervention Strategies ◽

Agent Based Model ◽

Agent Based ◽

Infected People ◽

Increase Risk ◽

The Impact

AbstractMany countries are implementing lockdown measures to slow the COVID-19 pandemic, putting more than a third of the world’s population under restrictions. The scale of such lockdowns is unprecedented, and while some effects of lockdowns are readily apparent, it is less clear what effects they may have on outbreaks of serious communicable diseases. We examine the impact of these lockdowns on outbreaks of mosquito-borne diseases. Using an agent-based model and simulations, we find that the risk and severity of such outbreaks is much greater under lockdown conditions, with the number of infected people doubling in some cases. This increase in number of cases varies by different mosquito-borne diseases, and is significantly higher for diseases spread by day-biting mosquitoes. We analysed various intervention strategies and found that during lockdowns, decentralised strategies such as insecticide-treated nets and indoor residual spraying are more effective than centralised strategies.

Lockdowns to Contain COVID-19 Increase Risk and Severity of Mosquito-Borne Disease Outbreaks

10.21203/rs.3.rs-22289/v1 ◽

2020 ◽

Author(s):

Akshay Jindal ◽

Shrisha Rao

Keyword(s):

Disease Outbreaks ◽

Intervention Strategies ◽

Agent Based Model ◽

Agent Based ◽

Infected People ◽

Increase Risk ◽

The Impact

Abstract Many countries are implementing lockdown measures to slow the COVID-19 pandemic, putting more than a third of the world’s population under restrictions. The scale of such lockdowns is unprecedented, and while some effects of lockdowns are readily apparent, it is less clear what effects they may have on outbreaks of serious communica-ble diseases. We examine the impact of these lockdowns on outbreaks of mosquito-borne diseases. Using an agent-based model and simu-lations, we find that the risk and severity of such outbreaks is much greater under lockdown conditions, with the number of infected people doubling in some cases. This increase in number of cases varies by dif- ferent mosquito-borne diseases, and is significantly higher for diseases spread by day-biting mosquitoes. We analysed various intervention strategies and found that during lockdowns, decentralised strategies such as insecticide-treated nets and indoor residual spraying are more effective than centralised strategies.

A Spatial Agent-Based Model to Assess the Spread of Malaria in Relation to Anti-Malaria Interventions in Southeast Iran

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9090549 ◽

2020 ◽

Vol 9 (9) ◽

pp. 549

Author(s):

Navid Mahdizadeh Gharakhanlou ◽

Navid Hooshangi ◽

Marco Helbich

Keyword(s):

Intervention Strategies ◽

Agent Based Model ◽

Malaria Endemic Area ◽

High Coverage ◽

Agent Based ◽

The World ◽

Coverage Rates ◽

Long Lasting Insecticidal Nets ◽

Malaria Interventions

Malaria threatens the lives of many people throughout the world. To counteract its spread, knowledge of the prevalence of malaria and the effectiveness of intervention strategies is of great importance. The aim of this study was to assess (1) the spread of malaria by means of a spatial agent-based model (ABM) and (2) the effectiveness of several interventions in controlling the spread of malaria. We focused on Sarbaz county in Iran, a malaria-endemic area where the prevalence rate is high. Our ABM, which was carried out in two steps, considers humans and mosquitoes along with their attributes and behaviors as agents, while the environment is made up of diverse environmental factors, namely air temperature, relative humidity, vegetation, altitude, distance from rivers and reservoirs, and population density, the first three of which change over time. As control interventions, we included long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS). The simulation results showed that applying LLINs and IRS in combination, rather than separately, was most efficient in reducing the number of infected humans. In addition, LLINs and IRS with moderate or high and high coverage rates, respectively, had significant effects on reducing the number of infected humans when applied separately. Our results can assist health policymakers in selecting appropriate intervention strategies in Iran to reduce malaria transmission.

Optimal (Control of) Intervention Strategies for Malaria Epidemic in Karonga District, Malawi

Abstract and Applied Analysis ◽

10.1155/2014/594256 ◽

2014 ◽

Vol 2014 ◽

pp. 1-20 ◽

Cited By ~ 5

Author(s):

Peter M. Mwamtobe ◽

Shirley Abelman ◽

J. Michel Tchuenche ◽

Ansley Kasambara

Keyword(s):

Optimal Control ◽

Control Strategies ◽

Public Health Problem ◽

Intervention Strategies ◽

Prevention Strategies ◽

African Region ◽

Infected People ◽

Malaria Epidemic

Malaria is a public health problem for more than 2 billion people globally. About 219 million cases of malaria occur worldwide and 660,000 people die, mostly (91%) in the African Region despite decades of efforts to control the disease. Although the disease is preventable, it is life-threatening and parasitically transmitted by the bite of the femaleAnophelesmosquito. A deterministic mathematical model with intervention strategies is developed in order to investigate the effectiveness and optimal control strategies of indoor residual spraying (IRS), insecticide treated nets (ITNs) and treatment on the transmission dynamics of malaria in Karonga District, Malawi. The effective reproduction number is analytically computed, and the existence and stability conditions of the equilibria are explored. The model does not exhibit backward bifurcation. Pontryagin’s Maximum Principle which uses both the Lagrangian and Hamiltonian principles with respect to a time dependent constant is used to derive the necessary conditions for the optimal control of the disease. Numerical simulations indicate that the prevention strategies lead to the reduction of both the mosquito population and infected human individuals. Effective treatment consolidates the prevention strategies. Thus, malaria can be eradicated in Karonga District by concurrently applying vector control via ITNs and IRS complemented with timely treatment of infected people.

Examining the impact of larval source management and insecticide-treated nets using a spatial agent-based model of Anopheles gambiae and a landscape generator tool

Malaria Journal ◽

10.1186/1475-2875-12-290 ◽

2013 ◽

Vol 12 (1) ◽

Cited By ~ 13

Author(s):

SM Niaz Arifin ◽

Gregory R Madey ◽

Frank H Collins

Keyword(s):

Anopheles Gambiae ◽

Agent Based Model ◽

Agent Based ◽

Larval Source Management ◽

The Impact ◽

Source Management

Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

Scientific Reports ◽

10.1038/s41598-020-79000-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Jonatan Almagor ◽

Stefano Picascia

Keyword(s):

High Rate ◽

Contact Tracing ◽

Agent Based Model ◽

Agent Based ◽

The Social ◽

Behavioural Factors ◽

The Impact ◽

Different Levels ◽

User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.