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Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing
Open accessAbstract
Significance: Widespread human impacts on the environment are expected to harm human health, which may in turn alter our interactions with the environment. However, evidence for impacts of environmental changes on health, and for feedbacks between environmental change and health, remains locally specific and context dependent. Using a large, geospatial dataset encompassing the Brazilian Amazon rainforest across 13 y, we identify strong evidence for a feedback between deforestation and malaria: Deforestation significantly increases malaria transmission, while high malaria burden simultaneously reduces forest clearing. Our results put into broader context the contradictory effects of deforestation on malaria found in earlier studies and provide evidence useful to land use policy and public health interventions that provide win–win solutions for conservation and health.
Overview
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Written from the paper’s full text.
TL;DR
Using 2003–2015 data from 795 Brazilian Amazon municipalities and instrumental-variable econometrics, the paper finds deforestation increases malaria incidence while malaria burden reduces forest clearing. These bidirectional effects are strongest in interior/frontier areas and attenuate where forest has already been cleared.
Key findings
- Deforestation significantly increased malaria incidence (β = 0.327, SE = 0.145, P = 0.024); the IV model predicted a 10% increase in deforestation (∼1,567 additional km² cleared Amazon-wide in 2008) would cause a 3.27% increase in malaria incidence (∼9,980 additional cases in 2008).
- The effect was larger in the interior and absent in outer Amazonian states: for *P. falciparum* in the interior, β = 0.716, SE = 0.323, P = 0.027; in outer states, β = 0.020, SE = 0.014, P = 0.136.
- Malaria burden significantly reduced forest clearing (β = −1.410, SE = 0.654, P = 0.031); a 1% increase in malaria incidence (∼3,024 additional cases in 2008) was expected to reduce deforestation by ∼1.41% (∼219 fewer km² lost in 2008).
- The negative effect of malaria on deforestation was consistent in the interior but disappeared in outer Amazonian states; malaria incidence also increased with precipitation and optimal dry-season temperature and decreased with population density and per capita GDP.
Methods
- Observational geospatial panel of 795 municipalities across the Brazilian Amazon from 2003 to 2015, using annual malaria incidence from SIVEP-Malaria, annual forest loss/cover from the Hansen Global Forest Change dataset, and covariates including population density, per capita GDP, temperature, and precipitation.
- Econometric analysis used OLS, least-squares dummy variable models with municipality and year fixed effects, and instrumental-variable/2SLS regression to address omitted-variable and simultaneity bias; deforestation was instrumented with dry-season aerosol pollution, and malaria was instrumented with optimal dry-season transmission temperature.
- Robustness checks included total, *P. vivax*, and *P. falciparum* malaria models; interior versus outer Amazonian state subsets; total forest loss versus loss near settlements; alternative temperature windows, precipitation measures, aerosol timing, and comparison with PRODES deforestation data.
Limitations
- The paper states that municipality-year aggregate data may mask local-scale and intraannual heterogeneity in environmental conditions and malaria transmission, and that the broad spatial-temporal scale trades off with resolution.
- The paper states that, as with all observational studies, it cannot be certain all possible confounding factors are captured, and the results do not directly identify the underlying mechanisms; local mechanistic studies are needed.
- Evident from the text: causal interpretation depends on the instrument exogeneity assumptions—that dry-season aerosol pollution affects malaria only through deforestation and that optimal transmission temperature is not otherwise related to deforestation—which the paper argues for but cannot fully prove.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
16 Own method · 10 Own interpretation · 10 Own result · 8 Sources not found · 1 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that deforestation, specifically measured as annual area of forest lost within a given municipality, significantly increased malaria incidence (β = 0.327, SE = 0.145, P = 0.024* [*indicates statistical significance at the P < 0.05 level]; Fig. 2 and SI Appendix, Table S1 and Fig. S1).”
- Also stated in: § Discussion · boosted
“Our work provides clear large-scale evidence that deforestation increases malaria, by using econometric techniques that approximate the gold standard of randomized controlled trials with observational data where controlled experiments are impossible.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Aerosol pollution is a valid instrument for deforestation (correlated with deforestation but not independently correlated with malaria).
- Also stated in: § Discussion · boosted
In the paper
“Additionally, parsing the Amazonian states into”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
What the sources say
- Not matchedcites [35]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We estimate a 1% increase in malaria incidence results in a 1.4% decrease in forest area cleared (∼219 fewer km 2 cleared associated with 3,024 additional cases in 2008).”
- Also stated in: § Results · hedged
“A 1% increase in malaria incidence (∼3,024 ad- ditional cases in 2008, for example) is expected to reduce de- forestation by ∼1.41% (∼219 fewer km 2 lost in 2008).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Abstract
hedgeddirectn = 3,024 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Optimal transmission temperature is plausibly exogenous to the larger economic and policy context that determines deforestation, making it a valid instrument for malaria.
- Also stated in: § Results · hedged
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“P. falciparum malaria had a stronger relationship with deforestation, while P. vivax malaria exhibited attenuated relationships with deforestation and other predictors, likely because this parasite can relapse months to years after initial infection, decoupling transmission from the onset of disease.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our results suggest a 10% increase in deforestation leads to a 3.3% increase in malaria incidence (∼9,980 additional cases associated with 1,567 additional km 2 lost in 2008, the study midpoint, Amazon-wide).”
- Also stated in: § Results · hedged
“The model that used aerosol pollution as an instrument for deforestation predicted that, on average, a 10% increase in deforestation (∼1,567 addi- tional km 2 cleared across the Amazon in 2008, the midpoint of the study, for example) would result in a 3.27% increase in malaria incidence (∼9,980 additional cases overall in 2008) (SI Appendix, Table S1).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Abstract
hedgeddirectn = 9,980 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Aerosol pollution is a valid instrument for deforestation (correlated with deforestation but not independently correlated with malaria).
- Also stated in: § Results · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At the same time, our work provides evidence for a socioecological feedback in which high malaria incidence simultaneously reduces forest clearing.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
boosteddirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, we find that the slope of the relationship is not significantly different from zero in the outer Amazonian states where most forest has already been cleared (β = 0.020, SE = 0.014, P = 0.136).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found strong evidence for a bidirectional feedback between deforestation and malaria: While deforestation increased malaria incidence, high malaria incidence in turn decreased the area of forest lost annually (β = -1.410,SE = 0.654, P = 0.031* [*indicates statistical significance at the P < 0.05 level]; Fig. 2 and SI Appendix, Tables S14-S17 and Fig. S8).”
- Also stated in: § Abstract · hedged
“increased malaria burden significantly reduces forest clearing, possibly mediated by human behavior or economic development.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Optimal transmission temperature is plausibly exogenous to the larger economic and policy context that determines deforestation, making it a valid instrument for malaria.
- Also stated in: § Abstract · hedged
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The negative effect of malaria on deforestation was robust to con- trolling for omitted variables (via dummy variables) that might also affect deforestation and spatial and temporal autocorrela- tion of the errors (SI Appendix, Tables S14-S17), across a variety of model specifications (SI Appendix, Tables S18-S25 and Figs.S6, S8, and S9).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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In the paper
“Here, we illustrate that deforestation exacerbates malaria transmission in the Brazilian Amazon, particularly in the highly forested regions in the early stages of land conversion.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
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- It may state two separate claims as one. 12
- Probably not a substantial claim. 9
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Malaria incidence also increased with precipitation and optimal temperature for transmission in the dry season, when most cases of malaria are transmitted, and decreased with population density and per capita gross domestic product (GDP) (SI Appendix, Table S1).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The effect is larger in the interior and absent in outer Amazonian states where little forest remains.”
- Also stated in: § Results · plain
“In contrast, we find that the slope of the relationship is not significantly different from zero in the outer Amazonian states where most forest has already been cleared (β = 0.020, SE = 0.014, P = 0.136).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“however, the quadratic term was not significant and did not substantially influence model results, so this specification was dropped.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Malaria and forest cover are highest in the interior of the Brazilian Amazon, while active deforestation and aerosol pollution peak at the interface between the forest interior and outer Amazonian states.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The key implication is that forest clearing has a direct impact on human health, in addition to the loss of other ecosystem services such as species diversity, water quality, and carbon storage, that is quantifiable and predictable at regional and decadal scales.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“The effects of deforestation on malaria are largest in the early stages of deforestation in the interior of the Amazon as forest edge habitat increases, promoting mosquito vector breeding habitat, survival, and human biting rate (5, 6, 15), but the effects attenuate as forest loss progresses, forest edge area declines, and human settlements become larger and further removed from forest (10,21).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
What the sources say
- Not matchedcites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [6]
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- Not matchedcites [15]
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- Not matchedcites [10]
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- Not matchedcites [21]
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plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“P. falciparum malaria had a stronger relationship with deforestation, while P. vivax malaria exhibited attenuated relationships with deforestation and other predictors, likely because this parasite can relapse months to years after initial infection, decoupling transmission from the onset of disease.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Results
hedgeddirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, we use aggregate data at the scale of municipalities at an annual time step, which may mask local-scale and intraannual heterogeneity in environmental conditions and malaria transmission.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Thus, while numerous other economic, political, social, and environmental factors play a much more substantial role in determining where and how much forest is cleared, here we find evidence that elevated malaria burden may also reduce rates of deforestation.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
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In the paper
“Our statistical approach controls for many possible confounding factors unique to municipalities, regions, and years, and is robust to a variety of different specifications and data subsets.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“However, as with all observational data studies, we cannot say with certainty that we capture all possible confounding factors that would otherwise preclude a causal interpretation of the results.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“Importantly, ignoring this statistically wellsupported feedback leads to substantial underestimates of the true effect of deforestation on malaria transmission, which may have confounded the results of earlier studies.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Discussion
hedgeddirect- Asserted: passes — The authors put it forward as true.
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What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“however, all control variables were retained in this first model (VIF < 10).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We also incorporate year dummy variables to control for year shocks shared by the Amazon basin (e.g., the global recession, changes in international commodity prices for beef or soy, changes in health or forest conservation policy) that may directly or indirectly influence malaria transmission from year to year across the study region.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Estimation Approach.
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In the paper
“we use municipality dummy variables that control for roughly time-invariant characteristics of municipalities (e.g., perennial water bodies, protected areas, elevation) for which we do not include or have data.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Estimation Approach.
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Probably not a substantial claim.
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In the paper
“Control variables are included to reduce bias from omitted variables, although these variables can exhibit high collinearity, which may produce unreliable coefficient estimates.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“We use microregion clusters (Fig. 1A) in the OLS (Eq.1), LSDV (Eq.2), and IV (Eq.4) models to account for spatial and temporal autocorrelation between municipalities within microregions, which were defined by”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
What the sources say
- Not matchedcites IBGE, https://www.ibge.gov.br/
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In the paper
“In particular, the parameter estimates are insensitive to the cluster specification with CRSEs, and thus remain consistent and unbiased even if the clusters are incorrectly specified (63).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
What the sources say
- Not matchedcites [63]
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plain- Asserted: passes — The authors put it forward as true.
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In the paper
“following evidence for endogeneity between deforestation and malaria obtained above, which suggests a possible effect of malaria on deforestation, we specified a series of models in the opposite direction to directly investigate this relationship.”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“We use cluster-robust SEs (CRSEs), which are robust to arbitrary within-cluster correlation in the errors as well as heteroscedasticity (62).”
§ Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing > Econometric Methods.
What the sources say
- Not matchedcites [62]
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plain- Asserted: passes — The authors put it forward as true.
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The paper relies on this without support.
Aerosol pollution is a valid instrument for deforestation (correlated with deforestation but not independently correlated with malaria).
“The model that used aerosol pollution as an instrument for deforestation predicted that, on average, a 10% increase in deforestation (∼1,567 addi- tional km 2 cleared across the Amazon in 2008, the midpoint of the study, for example) would result in a 3.27% increase in malaria incidence (∼9,980 additional cases overall in 2008) (SI Appendix, Table S1).”
The paper relies on this without support.
Optimal transmission temperature is plausibly exogenous to the larger economic and policy context that determines deforestation, making it a valid instrument for malaria.
“Our instrument for malaria, optimal transmission temperature, is plausibly exogenous to the larger economic and policy context that determines deforestation.”
The paper relies on this without support.
Aerosol pollution in September does not affect annual malaria incidence except through deforestation.
“unlikely to independently drive malaria transmission”
The paper relies on this without support.
Optimal temperature for transmission in the dry season is not otherwise related to deforestation.
“but not otherwise related to deforestation.”
“which is highly correlated with annual malaria incidence, as an instrument for malaria (see diagnostics in SI Appendix, Tables S15, S22-S24, and S27), but not otherwise related to deforestation.”
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Metadata
- Authors
- MacDonald, A. J., & Mordecai, E. A.
- Affiliations
- University of California, Santa Barbara (US)
- Stanford University (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2019-10-14
- Volume
- 116
- Issue
- 44
- Pages
- 22212-22218
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6825316
- OpenAlex
- W2980466780
- Semantic Scholar
- 459f1dce5682568561b0aba7bf92d1de0e752a11
- Cited by
- 250
- References
- 68
- Citations by year
- 2026: 30 · 2025: 35 · 2024: 38 · 2023: 38 · 2022: 35 · 2021: 48 · 2020: 25 · 2019: 1
- FWCI
- 25.09
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-08-10)
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (1611767, DEB-1518681)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Physical Sciences › Environmental Science › Global and Planetary Change › Conservation, Biodiversity, and Resource Management
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
- Keywords
- deforestation, malaria transmission, malaria burden, forest clearing, environmental health, environmental change and health, Amazon rainforest, land use policy
- MeSH terms
- Brazil, Conservation of Natural Resources, Humans, Malaria, Rainforest
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-03, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-03 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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