Parameter Sensitivity Analyses in Agent-Based Urban Growth Models

Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

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Analyzing the Spatiotemporal Uncertainty in Urbanization Predictions

Remote Sensing ◽

10.3390/rs13030512 ◽

2021 ◽

Vol 13 (3) ◽

pp. 512

Author(s):

Jairo Alejandro Gómez ◽

ChengHe Guan ◽

Pratyush Tripathy ◽

Juan Carlos Duque ◽

Santiago Passos ◽

...

Keyword(s):

Urban Growth ◽

Geographical Information Systems ◽

Growth Models ◽

A Priori ◽

Remote Sensing Data ◽

Public Utility ◽

Town Planning ◽

Geographical Information ◽

New Town ◽

Spatiotemporal Uncertainty

With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make investments, design infrastructure, extend public utility networks, plan housing solutions, and mitigate adverse environmental impacts. Despite its importance, urban growth models often discard the spatiotemporal uncertainties in their prediction estimates. In this paper, we analyzed the uncertainty in the urban land predictions by comparing the outcomes of two different growth models, one based on a widely applied cellular automata model known as the SLEUTH CA and the other one based on a previously published machine learning framework. We selected these two models because they are complementary, the first is based on human knowledge and pre-defined and understandable policies while the second is more data-driven and might be less influenced by any a priori knowledge or bias. To test our methodology, we chose the cities of Jiaxing and Lishui in China because they are representative of new town planning policies and have different characteristics in terms of land extension, geographical conditions, growth rates, and economic drivers. We focused on the spatiotemporal uncertainty, understood as the inherent doubt in the predictions of where and when will a piece of land become urban, using the concepts of certainty area in space and certainty area in time. The proposed analyses in this paper aim to contribute to better urban planning exercises, and they can be extended to other cities worldwide.

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Public health impact of delaying second dose of BNT162b2 or mRNA-1273 covid-19 vaccine: simulation agent based modeling study

BMJ ◽

10.1136/bmj.n1087 ◽

2021 ◽

pp. n1087

Author(s):

Santiago Romero-Brufau ◽

Ayush Chopra ◽

Alex J Ryu ◽

Esma Gel ◽

Ramesh Raskar ◽

...

Keyword(s):

Hospital Admissions ◽

Vaccination Strategy ◽

Population Based ◽

Agent Based Modeling ◽

Sensitivity Analyses ◽

Agent Based ◽

Cumulative Mortality ◽

Vaccination Rates ◽

Dose Strategy ◽

Modeling Study

AbstractObjectiveTo estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination.DesignSimulation agent based modeling study.SettingSimulated population based on real world US county.ParticipantsThe simulation included 100 000 agents, with a representative distribution of demographics and occupations. Networks of contacts were established to simulate potentially infectious interactions though occupation, household, and random interactions.InterventionsSimulation of standard covid-19 vaccination versus delayed second dose vaccination prioritizing the first dose. The simulation runs were replicated 10 times. Sensitivity analyses included first dose vaccine efficacy of 50%, 60%, 70%, 80%, and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread (that is, non-sterilizing vaccine); and an alternative vaccination strategy that implements delayed second dose for people under 65 years of age, but not until all those above this age have been vaccinated.Main outcome measuresCumulative covid-19 mortality, cumulative SARS-CoV-2 infections, and cumulative hospital admissions due to covid-19 over 180 days.ResultsOver all simulation replications, the median cumulative mortality per 100 000 for standard dosing versus delayed second dose was 226 v 179, 233 v 207, and 235 v 236 for 90%, 80%, and 70% first dose efficacy, respectively. The delayed second dose strategy was optimal for vaccine efficacies at or above 80% and vaccination rates at or below 0.3% of the population per day, under both sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100 000. The delayed second dose strategy for people under 65 performed consistently well under all vaccination rates tested.ConclusionsA delayed second dose vaccination strategy, at least for people aged under 65, could result in reduced cumulative mortality under certain conditions.

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A spatial zoning approach to calibrate and validate urban growth models

International Journal of Geographical Information Science ◽

10.1080/13658816.2016.1236927 ◽

2016 ◽

Vol 31 (4) ◽

pp. 763-782 ◽

Cited By ~ 41

Author(s):

Ali Kazemzadeh-Zow ◽

Saeed Zanganeh Shahraki ◽

Luca Salvati ◽

Najmeh Neisani Samani

Keyword(s):

Urban Growth ◽

Growth Models

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The Public Health Impact of Delaying a Second Dose of the BNT162b2 or mRNA-1273 COVID-19 Vaccine

10.1101/2021.02.23.21252299 ◽

2021 ◽

Author(s):

Santiago Romero-Brufau ◽

Ayush Chopra ◽

Alex J Ryu ◽

Esma Gel ◽

Ramesh Raskar ◽

...

Keyword(s):

Vaccination Strategy ◽

Population Level ◽

Health Impact ◽

Vaccination Rate ◽

Agent Based Modeling ◽

Sensitivity Analyses ◽

Agent Based ◽

Cumulative Mortality ◽

Vaccination Rates ◽

The Public

AbstractObjectivesTo estimate population health outcomes under delayedsecond dose versus standard schedule SARS-CoV-2 mRNA vaccination.DesignAgent-based modeling on a simulated population of 100,000 based on a real-world US county. The simulation runs were replicated 10 times. To test the robustness of these findings, simulations were performed under different estimates for single-dose efficacy and vaccine administration rates, and under the possibility that a vaccine prevents only symptoms but not asymptomatic spread.Settingpopulation level simulation.Participants100,000 agents are included in the simulation, with a representative distribution of demographics and occupations. Networks of contacts are established to simulate potentially infectious interactions though occupation, household, and random interactionsInterventionswe simulate standard Covid-19 vaccination, versus delayed-second-dose vaccination prioritizing first dose. Sensitivity analyses include first-dose vaccine efficacy of 70%, 80% and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread; and an alternative vaccination strategy that implements delayed-second-dose only for those under 65 years of age.Main outcome measurescumulative Covid-19 mortality over 180 days, cumulative infections and hospitalizations.ResultsOver all simulation replications, the median cumulative mortality per 100,000 for standard versus delayed second dose was 226 vs 179; 233 vs 207; and 235 vs 236; for 90%, 80% and 70% first-dose efficacy, respectively. The delayed-second-dose strategy was optimal for vaccine efficacies at or above 80%, and vaccination rates at or below 0.3% population per day, both under sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100,000. The delayed-second-dose for those under 65 performed consistently well under all vaccination rates tested.ConclusionsA delayed-second-dose vaccination strategy, at least for those under 65, could result in reduced cumulative mortality under certain conditions.

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Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran

Cities ◽

10.1016/j.cities.2013.01.005 ◽

2013 ◽

Vol 32 ◽

pp. 33-42 ◽

Cited By ~ 100

Author(s):

Jamal Jokar Arsanjani ◽

Marco Helbich ◽

Eric de Noronha Vaz

Keyword(s):

Urban Growth ◽

Agent Based Modeling ◽

Growth Patterns ◽

Agent Based ◽

Spatiotemporal Simulation

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Agent-Based Urban Modeling: Simulating Urban Growth and Subsequent Landscape Change in Suzhou, China

Urban Remote Sensing ◽

10.1002/9780470979563.ch24 ◽

2011 ◽

pp. 347-357 ◽

Cited By ~ 1

Author(s):

Yichun Xie ◽

Xining Yang

Keyword(s):

Urban Growth ◽

Landscape Change ◽

Urban Modeling ◽

Agent Based

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Modeling Urban Systems

The Oxford Handbook of Urban Planning ◽

10.1093/oxfordhb/9780195374995.013.0017 ◽

2012 ◽

pp. 322-351 ◽

Cited By ~ 2

Author(s):

John D. Landis

Keyword(s):

Land Use ◽

Urban Growth ◽

Travel Behavior ◽

Growth Models ◽

Urban Systems ◽

Economic Base ◽

Hedonic Price ◽

Hedonic Price Models ◽

Different Types ◽

Behavior Models

This article examines the different types of urban model used in urban planning in North America, and to a lesser extent, in Europe, Asia, and South Americam, which include the population-projection models, economic base models, hedonic price models, and travel-behavior models. It describes emerging procedures such as land-use change and urban-growth models, and looks at Charles Tiebout's model of efficient public choice and Thomas Schelling's model of spatial segregation.

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Cost-Effectiveness of Alternative Uses of Polyvalent Meningococcal Vaccines in Niger: An Agent-Based Transmission Modeling Study

Medical Decision Making ◽

10.1177/0272989x19859899 ◽

2019 ◽

Vol 39 (5) ◽

pp. 553-567

Author(s):

S. M. Niaz Arifin ◽

Christoph Zimmer ◽

Caroline Trotter ◽

Anaïs Colombini ◽

Fati Sidikou ◽

...

Keyword(s):

Cost Effectiveness ◽

Prediction Interval ◽

Cost Effective ◽

Sensitivity Analyses ◽

Transmission Model ◽

Agent Based ◽

Infant Vaccination ◽

Important Health ◽

Catch Up ◽

Routine Infant

Background. Despite the introduction of an effective serogroup A conjugate vaccine (MenAfriVac™), sporadic epidemics of other Neisseria meningitidis serogroups remain a concern in Africa. Polyvalent meningococcal conjugate (PMC) vaccines may offer alternatives to current strategies that rely on routine infant vaccination with MenAfriVac plus, in the event of an epidemic, district-specific reactive campaigns using polyvalent meningococcal polysaccharide (PMP) vaccines. Methods. We developed an agent-based transmission model of N. meningitidis in Niger to compare the health effects and costs of current vaccination practice and 3 alternatives. Each alternative replaces MenAfriVac in the infant vaccination series with PMC and either replaces PMP with PMC for reactive campaigns or implements a one-time catch up campaign with PMC for children and young adults. Results. Over a 28-year period, replacement of MenAfriVac with PMC in the infant immunization series and of PMP in reactive campaigns would avert 63% of expected cases (95% prediction interval 49%–75%) if elimination of serogroup A is not followed by serogroup replacement. At a PMC price of $4/dose, this would cost $1412 ($81–$3510) per disability-adjusted life-year (DALY) averted. If serogroup replacement occurs, the cost-effectiveness of this strategy improves to $662 (cost-saving, $2473) per DALY averted. Sensitivity analyses accounting for incomplete laboratory confirmation suggest that a catch-up PMC campaign would also meet standard cost-effectiveness thresholds. Limitations. The assumption that polyvalent vaccines offer similar protection against all serogroups is simplifying. Conclusions. The use of PMC vaccines to replace MenAfriVac in routine infant immunization and in district-specific reactive campaigns would have important health benefits and is likely to be cost-effective in Niger. An additional PMC catch-up campaign would also be cost-effective if we account for incomplete laboratory reporting.

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