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1.
Plowright RK, Reaser JK, Locke H, Woodley SJ, Patz JA, Becker DJ, Oppler G, Hudson PJ, Tabor GM, 2021. Land use-induced spillover: a call to action to safeguard environmental, animal, and human health. Lancet Planet Health 5: e237–e245.
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2.
Thomas MB, 2020. Epidemics on the move: climate change and infectious disease. PLoS Biol 18: e3001013.
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3.
Jones KE, Patel NG, Levy MA, Storeygard A, Balk D, Gittleman JL, Daszak P, 2008. Global trends in emerging infectious diseases. Nature 451: 990–993.
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4.
MacDonald AJ, Mordecai EA, 2019. Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing. Proc Natl Acad Sci USA 116: 22212–22218.
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5.
Valle D, Laporta GZ, 2021. A cautionary tale regarding the use of causal inference to study how environmental change influences tropical diseases. Am J Trop Med Hyg 104: 1960–1962.
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Larsen AE, Meng K, Kendall BE, 2019. Causal analysis in control–impact ecological studies with observational data. Methods Ecol Evol 10: 924–934.
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Bonds MH, Dobson AP, Keenan DC, 2012. Disease ecology, biodiversity, and the latitudinal gradient in income. PLoS Biol 10: e1001456.
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8.
MacDonald AJ, Larsen AE, Plantinga AJ, 2019. Missing the people for the trees: identifying coupled natural–human system feedbacks driving the ecology of Lyme disease. J Appl Ecol 56: 354–364.
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9.
Bauhoff S, Busch J, 2020. Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys. World Dev 127: 104734.
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10.
Jones IJ et al., 2020. Improving rural health care reduces illegal logging and conserves carbon in a tropical forest. Proc Natl Acad Sci USA 117: 28515–28524.
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11.
Garg T, 2019. Ecosystems and human health: the local benefits of forest cover in Indonesia. J Environ Econ Manage 98: 102271.
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12.
Couper LI, MacDonald AJ, Mordecai EA, 2021. Impact of prior and projected climate change on US Lyme disease incidence. Glob Change Biol 27: 738–754.
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13.
Larsen AE, MacDonald AJ, Plantinga AJ, 2014. Lyme disease risk influences human settlement in the wildland–urban interface: evidence from a longitudinal analysis of counties in the northeastern United States. Am J Trop Med Hyg 91: 747–755.
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Santos AS, Almeida AN, 2018. The impact of deforestation on malaria infections in the Brazilian Amazon. Ecol Econ 154: 247–256.
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Wooldridge JM, 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.
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16.
Morgan WT, Darbyshire E, Spracklen DV, Artaxo P, Coe H, 2019. Non-deforestation drivers of fires are increasingly important sources of aerosol and carbon dioxide emissions across Amazonia. Sci Rep 9: 16975.
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17.
Aragão LEOC et al., 2018. 21st century drought-related fires counteract the decline of Amazon deforestation carbon emissions. Nat Commun 9: 536.
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18.
Chen Y, Morton DC, Jin Y, Collatz G, Kasibhatla PS, van der Werf GR, DeFries RS, Randerson J, 2013. Long-term trends and interannual variability of forest, savanna and agricultural fires in South America. Carbon Manag 4: 617–638.
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19.
Hengl T, Wheeler I, 2018. Soil organic carbon content in × 5 g/kg at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution (Version v0.2). doi: 10.5281/zenodo.2525553.
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Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R, 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202: 18–27.
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Mordecai EA et al., 2012. Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecol Lett 16: 22–30.
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22.
Burke M, Hsiang SM, Miguel E, 2015. Global non-linear effect of temperature on economic production. Nature 527: 235–239.
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Cattelan AJ, Dall’Agnol A, 2018. The rapid soybean growth in Brazil. OCL 25: D102.
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Viana JS, Gonçalves EP, Silva AC, Matos VP, 2013. Climatic conditions and production of soybean in northeastern Brazil. IntechOpen. doi: 10.5772/52184.
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Olea JLM, Pflueger C, 2013. A robust test for weak instruments. J Bus Econ Stat 31: 358–369.
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Response to Valle and Zorello Laporta: Clarifying the Use of Instrumental Variable Methods to Understand the Effects of Environmental Change on Infectious Disease Transmission
Andrew J. MacDonald
Andrew J. MacDonald
Earth Research Institute and Bren School of Environmental Science and Management, University of California, Santa Barbara, California;
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Erin A. Mordecai
Erin A. Mordecai
Department of Biology, Stanford University, Stanford, California
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ABSTRACT.
Identifying the effects of environmental change on the transmission of vectorborne and zoonotic diseases is of fundamental importance in the face of rapid global change. Causal inference approaches, including instrumental variable (IV) estimation, hold promise in disentangling plausibly causal relationships from observational data in these complex systems. Valle and Zorello Laporta recently critiqued the application of such approaches in our recent study of the effects of deforestation on malaria transmission in the Brazilian Amazon on the grounds that key statistical assumptions were not met. Here, we respond to this critique by 1) deriving the IV estimator to clarify the assumptions that Valle and Zorello Laporta conflate and misrepresent in their critique, 2) discussing these key assumptions as they relate to our original study and how our original approach reasonably satisfies the assumptions, and 3) presenting model results using alternative instrumental variables that can be argued more strongly satisfy key assumptions, illustrating that our results and original conclusion—that deforestation drives malaria transmission—remain unchanged.
- Supplemental Materials (PDF 16 KB)
Author Notes
Financial support: A. J. M. and E. A. M. were supported by the National Science Foundation and the Fogarty International Center (DEB-2011147). E. A. M. was supported by the National Science Foundation (DEB-1518681), the National Institute of General Medical Sciences (R35GM133439), the Stanford King Center for Global Development, and the Terman Award.
Authors’ addresses: Andrew J. MacDonald, Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, E-mail: andy.j.macdon@gmail.com. Erin A. Mordecai, Department of Biology, Stanford University, Stanford, CA, E-mail: emordeca@stanford.edu.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
Plowright RK, Reaser JK, Locke H, Woodley SJ, Patz JA, Becker DJ, Oppler G, Hudson PJ, Tabor GM, 2021. Land use-induced spillover: a call to action to safeguard environmental, animal, and human health. Lancet Planet Health 5: e237–e245.
-
2.
Thomas MB, 2020. Epidemics on the move: climate change and infectious disease. PLoS Biol 18: e3001013.
-
3.
Jones KE, Patel NG, Levy MA, Storeygard A, Balk D, Gittleman JL, Daszak P, 2008. Global trends in emerging infectious diseases. Nature 451: 990–993.
-
4.
MacDonald AJ, Mordecai EA, 2019. Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing. Proc Natl Acad Sci USA 116: 22212–22218.
-
5.
Valle D, Laporta GZ, 2021. A cautionary tale regarding the use of causal inference to study how environmental change influences tropical diseases. Am J Trop Med Hyg 104: 1960–1962.
-
6.
Larsen AE, Meng K, Kendall BE, 2019. Causal analysis in control–impact ecological studies with observational data. Methods Ecol Evol 10: 924–934.
-
7.
Bonds MH, Dobson AP, Keenan DC, 2012. Disease ecology, biodiversity, and the latitudinal gradient in income. PLoS Biol 10: e1001456.
-
8.
MacDonald AJ, Larsen AE, Plantinga AJ, 2019. Missing the people for the trees: identifying coupled natural–human system feedbacks driving the ecology of Lyme disease. J Appl Ecol 56: 354–364.
-
9.
Bauhoff S, Busch J, 2020. Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys. World Dev 127: 104734.
-
10.
Jones IJ et al., 2020. Improving rural health care reduces illegal logging and conserves carbon in a tropical forest. Proc Natl Acad Sci USA 117: 28515–28524.
-
11.
Garg T, 2019. Ecosystems and human health: the local benefits of forest cover in Indonesia. J Environ Econ Manage 98: 102271.
-
12.
Couper LI, MacDonald AJ, Mordecai EA, 2021. Impact of prior and projected climate change on US Lyme disease incidence. Glob Change Biol 27: 738–754.
-
13.
Larsen AE, MacDonald AJ, Plantinga AJ, 2014. Lyme disease risk influences human settlement in the wildland–urban interface: evidence from a longitudinal analysis of counties in the northeastern United States. Am J Trop Med Hyg 91: 747–755.
-
14.
Santos AS, Almeida AN, 2018. The impact of deforestation on malaria infections in the Brazilian Amazon. Ecol Econ 154: 247–256.
-
15.
Wooldridge JM, 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.
-
16.
Morgan WT, Darbyshire E, Spracklen DV, Artaxo P, Coe H, 2019. Non-deforestation drivers of fires are increasingly important sources of aerosol and carbon dioxide emissions across Amazonia. Sci Rep 9: 16975.
-
17.
Aragão LEOC et al., 2018. 21st century drought-related fires counteract the decline of Amazon deforestation carbon emissions. Nat Commun 9: 536.
-
18.
Chen Y, Morton DC, Jin Y, Collatz G, Kasibhatla PS, van der Werf GR, DeFries RS, Randerson J, 2013. Long-term trends and interannual variability of forest, savanna and agricultural fires in South America. Carbon Manag 4: 617–638.
-
19.
Hengl T, Wheeler I, 2018. Soil organic carbon content in × 5 g/kg at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution (Version v0.2). doi: 10.5281/zenodo.2525553.
-
20.
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R, 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202: 18–27.
-
21.
Mordecai EA et al., 2012. Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecol Lett 16: 22–30.
-
22.
Burke M, Hsiang SM, Miguel E, 2015. Global non-linear effect of temperature on economic production. Nature 527: 235–239.
-
23.
Cattelan AJ, Dall’Agnol A, 2018. The rapid soybean growth in Brazil. OCL 25: D102.
-
24.
Viana JS, Gonçalves EP, Silva AC, Matos VP, 2013. Climatic conditions and production of soybean in northeastern Brazil. IntechOpen. doi: 10.5772/52184.
-
25.
Olea JLM, Pflueger C, 2013. A robust test for weak instruments. J Bus Econ Stat 31: 358–369.
| Past two years | Past Year | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 730 | 254 | 66 |
| Full Text Views | 238 | 124 | 2 |
| PDF Downloads | 74 | 11 | 2 |