PUBH5551 Chap.8 Biodiversity, Zoonoses and Infectious Disease
Biodiversity, Zoonoses and Infectious Disease
Climate and ecosystem change can alter vector, waterborne, foodborne and zoonotic disease pathways, but temperature alone does not determine transmission. This chapter connects climate suitability, habitat, vectors or pathogens, population behaviour, infrastructure and services. It also designs an early-warning chain that links surveillance to a prepared decision.
What this chapter covers
- 01
Temperature, rainfall and pathogen suitability
- 02
Vectors, hosts and ecosystem change
- 03
Waterborne and foodborne disease pathways
- 04
Land use, mobility and human contact
- 05
Disease and entomological surveillance
- 06
Climate-informed early warning and response
Worked example · free
Design a mosquito-borne disease warning chain
- +1Define the disease outcome, local transmission status and surveillance population.
- +1Combine weather and vector measures with explicit lags and seasonal baselines.
- +1Account for travel-associated cases, testing, reporting, immunity and control activity.
- +1Set thresholds that trigger source reduction, communication, clinician alerts and diagnostic readiness.
- +1Assess reach and feasibility for populations with unequal service and prevention access.
- +1Evaluate lead time, sensitivity, false alerts, action taken and cases prevented.
Key terms
- Vector-borne disease
- Disease transmitted by organisms such as mosquitoes or ticks between hosts.
- Zoonosis
- An infection transmitted naturally between vertebrate animals and humans.
- Climate suitability
- Environmental conditions that permit pathogen, vector or host processes relevant to transmission.
- Entomological surveillance
- Monitoring of insect vectors, including abundance, distribution and infection indicators.
- Early warning system
- Monitoring and communication linked to a prepared action before expected harm.
Biodiversity, Zoonoses and Infectious Disease FAQ
Does warming always increase infectious disease?
No. Temperature and rainfall can change suitability, but transmission also depends on vectors or pathogens, hosts, mobility, behaviour, water and sanitation, immunity, control and healthcare. Some relationships are nonlinear or location-specific. State the pathway and evidence rather than making a universal claim.
How can biodiversity affect disease risk?
Ecosystem change can alter host and vector communities, predators, breeding sites, microclimates, water filtration and human contact. The effect varies by disease and place. Avoid claiming biodiversity always reduces risk; identify the mechanism and the evidence supporting it in the relevant system.
What makes an early-warning system effective?
It needs reliable monitoring, enough lead time, clear communication, accountable recipients and a feasible pre-agreed response. Evaluation should include false alerts, reach, action taken and health outcomes. Forecast accuracy alone is insufficient if no protective action follows.
Assessment move
Build a disease triangle with climate and ecosystems, pathogen or vector, and population or place. Add surveillance and services as modifiers. Apply it separately to a vector-borne, waterborne and foodborne example. Practise distinguishing suitability, introduction, established transmission and detected cases.
For evidence critique, check time lags, diagnostic and reporting changes, human movement, control activity and the scale of climate data. When proposing warning systems, specify the decision threshold, recipient and action before discussing the model. Use equity questions about water, housing, occupation, prevention and diagnostic access.
The chapter is secure when you can explain why a climate signal matters without presenting it as a sufficient cause of disease. Strengthen revision by making separate causal diagrams for dengue, a waterborne infection and a foodborne infection. Use climate variables only where the biological or infrastructure mechanism is clear.
Add land use, mobility, immunity, testing, reporting and control as relevant, then mark the expected lag between stages. For each diagram, choose a surveillance indicator and a pre-agreed action. Compare a forecast metric such as sensitivity with a public-health metric such as timely intervention or prevented cases. This prevents model accuracy from standing in for programme effectiveness.
During source appraisal, check whether the study observes local transmission or only suitability, whether cases are confirmed, and whether surveillance effort changed. For quiz practice, sort statements into climate signal, vector or environmental signal, human exposure, health outcome and response.
For the major essay, explain how laboratory, workforce, water, housing and primary-care capacity shape feasibility in the selected country. Include a plan for false alerts and community trust. Finish by writing a bounded conclusion that identifies climate as one contributor, names the other necessary conditions and states the decision the evidence can reasonably support.
Complete a surveillance-design drill using a disease for which climate suitability is projected to change. Choose an environmental signal, a clinical or laboratory indicator, the spatial unit, update interval and decision threshold. Specify the action that follows an alert and the cost of a false positive and false negative.
Add a communication plan for communities and clinicians, including how uncertainty will be revised as observations accumulate. This makes clear that a forecast has public-health value only when it is connected to timely capacity, trusted reporting and a proportionate response.
