Changing Geographic Distribution of Malaria with Global Climate Warming

Contributor
Carleton College Teaching Activity Collection Kendra Murray Mary Savina
Type Category
Instructional Materials
Types
Activity , Graph , Numerical/Computer Model
Note
This resource, vetted by NSTA curators, is provided to teachers along with suggested modifications to make it more in line with the vision of the NGSS. While not considered to be “fully aligned,” the resources and expert recommendations provide teachers with concrete examples and expert guidance using the EQuIP rubric to adapted existing resources. Read more here.

Reviews

Description

In this exercise, students analyze climate data to find areas in the southern United States that are now close to having conditions in which the malaria parasite and its mosquito hosts thrive and then attempt to forecast when areas might become climatically suitable.

 

Students analyze climatic data from six different locations in the southern United States to determine if there could be a resurgence in malaria. Students must manipulate the data, using Excel, to generate eight graphs they use to analyze their specific location. After each location’s analysis is presented, students must evaluate all of the data and compare to the findings of a scientific research paper (http://science.sciencemag.org/content/289/5485/1763) for agreement or disagreement. You will need to register for a free account with AAAS to view the article.

 

The suggested timeline for this activity is two weeks. Suggested amounts of time needed for each of the parts of this exercise are found on the website. Students will need advanced math and computer skills for this activity. This may be best suited for an advanced class.

Intended Audience

Educator
Educational Level
  • Grade 12
  • Grade 11
Language
English
Access Restrictions

Free access - The right to view and/or download material without financial, registration, or excessive advertising barriers.

Performance Expectations

HS-ESS3-6 Use a computational representation to illustrate the relationships among Earth systems and how those relationships are being modified due to human activity.

Clarification Statement: Examples of Earth systems to be considered are the hydrosphere, atmosphere, cryosphere, geosphere, and/or biosphere. An example of the far-reaching impacts from a human activity is how an increase in atmospheric carbon dioxide results in an increase in photosynthetic biomass on land and an increase in ocean acidification, with resulting impacts on sea organism health and marine populations.

Assessment Boundary: Assessment does not include running computational representations but is limited to using the published results of scientific computational models.

This resource is explicitly designed to build towards this performance expectation.

Comments about Including the Performance Expectation
Students analyze climatic data from six locations in the southern United States to determine if there could be a resurgence in malaria due to changes in temperature and precipitation. Students use Excel (or another similar spreadsheet program) to generate eight graphs for the location they are assigned. They create a presentation of this location, discuss it with the class, and create a paper combining all six locations explaining their prediction about possible future malaria outbreaks. They have to identify if their predictions match that of a scientific article, The Global Spread of Malaria in a Future, Warmer World, by Randolph and Rogers. Links to human activity may be considered by the students at the end of the Sixth Assignment when they are directed to consider ethical and relative risk questions addressing the use of pesticides and best practices of malaria prevention.

Science and Engineering Practices

This resource is explicitly designed to build towards this science and engineering practice.

Comments about Including the Science and Engineering Practice
Students develop a Powerpoint (or other similar presentation) analyzing their graphical data and determining if it matches the predictions of Randolph and Rogers. They identify if there are any problems with the data. After their interpretations have been reviewed by their peers, and they receive feedback, students make revisions before submitting their work to the course folder. The summary paper students develop based on the information of all six locations, requires that students assume that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future. Students must take into consideration whether overall trends in both temperature and precipitation will continue to prevail in the future in order to determine the likelihood of potential malaria outbreaks. Students must also assume that the environmental requirements of the Plasmodium parasite will remain constant. The analysis question prompts should ensure that students achieve this portion of the science and engineering practice.

This resource is explicitly designed to build towards this science and engineering practice.

Comments about Including the Science and Engineering Practice
Students use Excel to extrapolate data from the United States Historical Climatology Network to analyze temperature and precipitation changes. Students determine average minimum and maximum temperature and monthly rainfall over the course of twelve months using at least thirty years of data. They must convert the data from English measurement to SI measurement. They determine if their data has a normal distribution as well as determine the moving average. They generate eight graphs they will use for their explanation of the probability of possible malaria outbreaks in south eastern United States.

Disciplinary Core Ideas

This resource is explicitly designed to build towards this disciplinary core idea.

Comments about Including the Disciplinary Core Idea
Students examine temperature and precipitation data to identify overall trends. They use this information to predict the likelihood of increased cases of malaria due to changing climate conditions making it more favorable for the malaria parasite, Plasmodium, to survive. While the activity does not discuss the reason behind why there are the atmospheric changes, it does spend a great deal of time looking at how changes in climate affect the biosphere. Other activities into what human activities are causing the atmosphere and ocean to become modified, like Earth’s Dynamically Changing Planet (http://ngss.nsta.org/Resource.aspx?ResourceID=541), could be introduced to fully cover this Disciplinary Core Idea.

Crosscutting Concepts

This resource is explicitly designed to build towards this crosscutting concept.

Comments about Including the Crosscutting Concept
Students use data to help predict the likelihood of future malaria outbreaks in several places in the southern United States. They must identify limitations of their data, and that of other scientific research, when making their predictions. Students discuss ambiguities and uncertainties of their climate data when evaluating all six locations in their final paper.

Resource Quality

  • Alignment to the Dimensions of the NGSS: Students must engage in two Science and Engineering Practices: mathematical and computational thinking and constructing explanations and designing solutions, to make sense of the potential resurgence of malaria in the southern United States. Students are engaged in mathematical and computational thinking when they analyze climatic data to give support to their evaluation of potential for malaria outbreaks. Students are engaged in constructing explanations when they develop their summary paper claims. Students use the Disciplinary Core Idea, Global Climate Change, to study how atmospheric changes affect the Plasmodium parasite’s geographic distribution. Students examine temperature and precipitation data to identify overall trends. They use this information to predict the likelihood of increased cases of malaria due to changing climate conditions making it more favorable for the malaria parasite, Plasmodium, to survive. Students use the Crosscutting Concept, systems and system models, when they identify limitations of their data, and that of other scientific research, when making their predictions. Students discuss ambiguities and uncertainties of their climate data when evaluating all six locations in their final paper. Students generate several graphs they use in order to create a model to predict if conditions will be favorable for Plasmodium. Not only are they identifying a system, and developing a model, students must also identify uncertainties in their model and another scientific model. Students use all three dimensions of the Next Generation Science Standards to generate their final analysis of all the data in their papers. In order for students to predict if there will be more malaria outbreaks in parts of the southern United States, they must use their data and corresponding model, created using Excel, as well as their understanding of how atmospheric changes can affect the geographic distribution of the Plasmodium parasite’s habitat. Students must also consider limitations of the model when creating their predictions.

  • Instructional Supports: Students are introduced to what malaria is in the introductory reading. Students may not live in the southern United States, but may travel there at some point, so knowing about potential risk for disease will be important to them. This is especially relevant in today's age with other emerging, mosquito-borne diseases like Zika virus. Students may not have had experience with malaria, but may have experience with other diseases like West Nile or Lyme Disease. Students may wish to investigate the spread of these diseases in response to changing global climate after doing this activity. Students work with actual climate data to identify the potential spread of malaria to the southern United States. Students should have some prior knowledge of how insect-borne diseases are spread. This activity builds on that prior knowledge by having them investigate the conditions needed for more favorable disease transmission. The data is scientifically accurate. Some students may need help understanding the scientific articles referenced in the activity. Teachers could point students to various graphs to help students understand the concepts in the papers. Students are presented with several opportunities for peer and teacher feedback throughout the exercise. No suggestions for connections to students home, neighborhood, community and/or culture are included. No alternatives for English language learners or students below reading level are included. Included in the teaching notes and tips is a suggestion for teachers to help students that may struggle with large data sets. Teachers may want to have an example station completed so students have an idea of what they should generate from the data and in their Powerpoint. Possible extensions are included in the final report guidance. Students may wish to address ethical and relative risk questions related to malaria and climate.

  • Monitoring Student Progress: Teachers have evidence of three dimensional learning in the student developed Powerpoint and final paper. Students must use all three dimensions of the Next Generation Science Standards to develop their location and overall analysis. Formative assessments, although not specifically identified as such, are found throughout the exercise. Students must generate an idea of what they need to look for in data analysis after reading the initial background information, how missing data may affect results, characterization of their location’s general climate, and their Powerpoint presentations. No rubrics or scoring guides are provided. It would be up to the teacher to develop any rubrics or scoring guides. Assessment of student’s proficiency uses a variety of methods that are accessible and unbiased for all students.

  • Quality of Technological Interactivity: Students will need access to a computer with Excel to do data analysis and generate their presentations and papers.