Epidemiology Flashcards
(126 cards)
1
Q
What is the formula for relative risk and odds ratio?
A
Relative risk:
Number of exposed cases/ (Number of exposed cases + number of exposed controls)/Number of not exposed cases/(Number of not exposed cases + number of not exposed controls)
Odds ratio:
(Number of exposed cases x Number of not exposed controls)/ (Number of exposed controls x Number of not exposed cases)
2
Q
Compare the advantages and disadvantages of case-control and cohort studies
A
Case-control: good for rare diseases, quicker and cost-effective, but recall bias and uncertain exposure-disease time relationship
Cohort: can study multiple outcomes simultaneously and eliminate bias if prospective, but inefficient for rare disease and loss-to-follow-up introduces bias
3
Q
Compare the advantages and disadvantages of high-risk and population public health interventions
A
High risk: effective and efficient, with strong benefit:risk ratio, but is temporary, difficult to perform and risk prediction may not be accurate
Population: equitable and larger potential but questionable benefit:risk ratios and poorer motivation
4
Q
Define a clinical trial
A
Clinical Trial: planned human experiment to measure effectiveness of intervention - not observational
5
Q
Define age standardised death rates
A
Age standardised death rates: rate of death per year, either for a given condition or for the population as a whole; can be used to assess the effectiveness of a country’s health system as well as comparing if one population is dying of a given condition more frequently than the other
6
Q
Why is caution warned with age standardised death rates?
A
Caution: differences in reporting, diagnostics, coding, and behaviour can all affect SMRs and cause “alarming increases” that do not actually translate to massively increased incidence or mortality
7
Q
What are the key features required for a clinical trial?
A
Key features: defined intervention, comparator, inclusion criteria and exclusion criteria
8
Q
Define and give the formula for sensitivity
A
Sensitivity: probability those WITH disease are identified (disease identified/disease total) - higher better
SnNout: when a test has a high sensitivity, a negative result tends to be in the diagnosis
9
Q
Define and give the formula for specificity
A
Specificity: probability those WITHOUT disease are identified (healthy identified/healthy total) - higher better
SpPin: when a test has a high specificity, a positive result tends to be in the diagnosis
10
Q
Define and give the formula for positive predicted values
A
+ve PV: probability those testing positive DO have the disease (positives true/positives total)
11
Q
Define and give the formula for negative predicted values
A
-ve PV: probability those testing negative DO NOT have the disease (negatives true/negatives total)
12
Q
Define and interpret p values
A
P-Value: likelihood that the result is due to chance, so p = 0.05 suggests that the probability of being the result of chance is 5%; p<0.05 is usually used as a test of significance, whereby if p<0.05 the probability the result is due to chance is less than 5%
13
Q
Define and interpret confidence intervals
A
Confidence intervals: repeated sampling will produce a spread of estimates around the true value, and 95% confidence intervals can be used to show where 95% of sample estimates will lie; this allows us to be confident that the true value lies somewhere within this interval
14
Q
Define and state the formula for relative risk
A
Relative risk: ratio of probability of an outcome in exposed group versus unexposed : incidence exposed / incidence unexposed
15
Q
Define and state the formula for attributable risk
A
Attributable risk: difference between rate of outcome in exposed and unexposed (hence attributable to exposure): (incidence exposed - incidence unexposed)/100
16
Q
Define and state the formula for odds ratio
A
Odds ratio: likelihood of having an exposure if you have the disease, relative to likelihood if you don’t have disease: odds cases / odds controls
17
Q
Define case control studies
A
Start with a source population, containing a group of cases and a group of controls from a population that is the same as/representative of that which the cases come from; looking retrospectively, compare the odds of exposure in those with the disease and those without, to see if those that have the disease were more likely to have been exposed - this will produce an ODDS RATIO
18
Q
Define cohort studies
A
These can be performed retrospectively (possibility of bias, less expensive) or prospectively (less bias, more expensive), and involve starting with a HEALTHY cohort of volunteers, and following them up over time to study the effect of exposure on outcomes. The cohort is divided at analysis to the exposed and unexposed, and then the risk of the outcome in question is studied to provide a RELATIVE RISK (incidence exposed/incidence unexposed)
19
Q
Define confounding
A
Confounder: a factor (e.g. Age, sex, ethnicity, socioeconomic status) that is associated with both the exposure of interest and the outcome of interest
20
Q
Define heterogeneity when conducting a meta analyses/ systematic review
A
Studies differ with respect to PICOS, and I2 can measure heterogeneity of included studies where 0% is fully homogeneous, 50% moderate heterogeneity and 75% classed as very hetergeneous
21
Q
Define high risk
A
High-risk: identifying those at most risk of disease and targeting with an intervention (screening at risk groups)
22
Q
Define population public health interventions
A
recognising common disease and targeting everyone to reduce exposure
23
Q
Define incidence
A
Incidence: number of new cases of a disease in a specified time period (number of cases/number disease free at beginning of period)
24
Q
What is prevalence?
A
Prevalence: number of cases of disease at a specific point in time (number of cases/total population)
25
What is mortality?
Mortality: the number of deaths due to a specific disease/condition in a specified time period (number of deaths/population at start of time period) - usually measured as deaths/1000 people per year
26
What is morbidity?
Morbidity: the number of cases of ill health, complications and side effects attributed to a particular condition over a given time period
27
Define null hypothesis, hypothesis and the role of statistical hypothesis testing
Null hypothesis (H0): there is no significant finding
Hypothesis (H1): there is a significant finding
Statistical hypothesis testing: in order to reject H0 we must be sure that the impact of chance is minimal, usually taken to be less than 5% (p<0.05); overlapping confidence intervals suggest that chance may be responsible for any apparent difference
28
Define odds ratio and the formula to calculate this
Odds ratio: compares likelihood someone with disease was exposed compared to someonte that does not e.g. if lung cancer has OR 4.5 for smoking, they are 4.5x more likely to have smoked than those without
Formula: (affected + exposed/affected + unexposed) / (unaffected + unexposed/unaffected + exposed)
29
Define routine data
Routine data: are collected routinely without a research question in mind, often for administrative or statutory purposes
30
Define coding
Coding: health outcomes such as deaths, adverse effects, admissions, procedures etc. are often given unique codes (e.g. Under a system such as ICD10) to allow for classification and comparison, but these can change, and reporting is not always standardised
31
Define sampling
Sampling: taking a representative group that is smaller than the whole population in order to study these individuals to establish prevalence, incidence or risks of the population as a whole
32
Define sampling variation
Sampling variation: due to variation within the population, and the random nature of sampling, chance will impact on any results, yet repetitive sampling will produce estimates centred around the true population risk
33
Define screening
Screening: investigating apparently healthy individuals with the objective of detecting unrecognised disease/precursors to prevent/delay development
34
What makes the perfect screening test?
Perfect test: no false positives, no false negatives (very unlikely)
35
Define selection bias
Selection Bias: systematic differences between those selected for study and those not e.g. Pre-existing risk factors, health conditions, behaviours, characteristics etc.
36
Define measurement bias
Measurement Bias: inaccurate measurements or classifications
37
Define recall bias
Recall Bias: failure of a study participant to accurately recall the level of exposure, either deliberately or by accidence
38
Define standardised mortality rates
SMR: ratio between number of deaths in population and those that would be expected for age and sex
39
What is the formula for standardised mortality rates and how can this be interpreted?
Calculation: observed deaths / expected deaths
Interpretation: SMR < 1.0 = 1 fewer than expected deaths, = 1.0 has the same number of expected deaths, > 1.0 had more than expected deaths
40
Define systematic review
Systematic review: answer a very specific question; all published literature is considered, and studies that are appropriate are selected and evaluated, and the data is reported to provide a definitive answer
41
Define meta analyses
Meta-analysis: use of statistical methods to summarise the results of the selected studies, weighting by how well performed and powerful the study was; publication bias can be assessed with a funnel plot; generates a pooled risk estimate
42
Define the experimental event rate
Experiment Event Rate (EER): incidence (of negative outcome trying to prevent) in the intervention arm
43
Define the control event rate
Control Event Rate (CER): incidence (of negative outcome trying to prevent) in the control arm
44
What is required to classify an intervention as successful?
Successful intervention: EER < CER
45
Define the number needed to treat and how this can be calculated from the CER and EER
NNTT: number needed to treat to avoid one additional negative outcome
1/ARR
(where ARR = CER-EER)
46
Define type 1 and type 2 errors and the power of a study
Type 1 error: false positives (alpha)
Type 2 error: false negatives (beta)
Power: 1 - beta (%) - usually 80-90%
47
Define validity for screening tests
Ability to distinguish between subjects with the condition and those who do not
48
Demonstrate application of epidemiological skills to clinical decision making
- Use an RCT or better an SR/MA when making clinical decisions about an individual patient
- Use an ecological study to make geographical comparisons
- Use a case-control or cohort study to examine risk factors
- Use case series/reports when dealing with very rare conditions
49
Described allocation bias
Allocation bias: volunteers may not be randomly allocated to placebo and treatment groups, and as such confounding variables may influence the results
50
Define measurement bias
Measurement bias: if the investigation team has pre-conceived ideas or a vested interest, they may subconsciously interpret the results differently - need double-blinding
51
Define reporting bias
Reporting bias: negative and neutral trials are unlikely to be reported, especially if commercially embarrassing
52
Define analysis bias
Analysis bias: if differential discontinuation occurs (more participants withdraw from one group than the other e.g. because of side effects), this can skew the analysis to show a larger than accurate benefit, so intention to treat analysis is needed
53
Describe interactions between incidence, prevalence and mortality
- If you introduce a treatment for a disease, this may DECREASE the mortality, but will INCREASE the prevalence, because those affected will not die from it
- If you introduce a treatment for a disease that prevents transmission e.g. ART in HIV, then this will DECREASE the incidence, as the spread is reduced, but the prevalence will INCREASE because fewer people die
- If the mortality of a condition decreases, but the incidence remains the same, the prevalence will INCREASE, because people will not die
54
Describe the current burden of infectious diseases and their disparities worldwide
Burden: the diseases with the highest mortality are lower respiratory infections, but closely followed by HIV/AIDS
Disparities: much more common in the developing world, and in sub-saharan Africa, infectious disease is the leading cause of death; this is due to poor sanitation and reduced access to healthcare and medication
55
Describe the global burden of cancer and list risk factors
Burden: 15% deaths worldwide, shifting to LEDCs
Risk factors: smoking, alcohol use, unsafe sex, obesity, low fruit/veg, inactivity, air pollution, indoor smoke, contaminated injections
56
Describe the phases of a clinical trial
Phase 1: SAFETY - small no. healthy volunteers
Phase 2: BIO EFFECT - few hundred with condition - safety and short term effect
Phase 3: EFFECTIVENESS - several thousand - comparing effectiveness and side effects to current/placebo
57
Describe the problems posed to SRs/MAs by publication bias and incompleteness
Incompleteness: may not be able to access all data due to lack of publication/language etc.
Publication Bias: only a subset of relevant data available; null and non-significant findings less likely to be reported and published; funnel plot can be used to determine bias, with a symmetrical plot showing no bias
58
Describe the public health prevention paradox
Most cases of disease come from populations where most have LOW risk, and few have HIGH risk; in order to reduce disease have to target everyone, preventing disease in FEW and inconveniencing MANY
59
Describe the role and appearance of a funnel plot
Shows the relationship between sample size and risk ratios - tends to converge to a point at the largest sample size - the true risk ratio; any gaps lower down indicate publication bias
60
Evaluate case-control for answering research question
Case-control studies: appropriate determining what causes rare diseases, but are not as good evidence as an RCT because are observational and may be strongly affected by confounders; only suggest an association between exposure and disease
61
Evaluate cohort studies for answering research questions
Cohort studies: higher on the hierarchy of evidence, and relative risk carries more weight than an odds ratio; are appropriate to answer research questions that seek to quantify the effect that exposure to a risk factor has on specific outcomes; it can be used to challenge suspected associations between cause and effect
62
Explain epidemiological transition
Global change in the levels and causes of mortality, summarised as a decline in total mortality and a significant reduction in infectious/deficiency disease alongside an increase in the relative role of chronic non-communicable diseases like cancers, cardiovascular disease, chronic respiratory disease and diabetes
63
Explain how an SR research question should be constructed
USE PICOS
Population
Intervention - exact intervention studied
Comparison
Outcomes - clinical/QOL?
Study design - RCTs/cohort/case-controls etc
64
Explain the clinical importance of incidence, prevalence and mortality and how these may be measured
Prevalence and incidence of disease can be used at population level for resource allocation and disease surveillance
Mortality and prevalence can be estimated using data from health records and death certificates (although you need to be careful of coding e.g. ICD10)
65
Explain the need to balance screening test cut off points
Raising the "abnormal" cut-off will exclude all false positives but will increase false negatives
Lowering the "abnormal" cut-off will exclude all false negatives but increase false positives
66
Explain the process of critical appraisal
Critical appraisal: systematic examination of research to assess validity, results and relevance before using to inform a decision
Method used: should be systematic, logical, empirical and replicable
Review checklists: can be used for critical appraisal of study types e.g. CONSORT (RCT) and STROBE (observational)
67
Explain the use of a forest plot
Can be used to show pooled risk ratios; triangle at base is pooled risk, and if overlaps 1.0 then is not significant
68
Explain three methods for dealing with confounding
Stratification: splitting the analysis of the data by subgroups (strata e.g. age/sex) to exclude the impact of these confounders to show if any difference is the result of exposure; simple to perform, but limit on the number of factors that can be stratified (as number of strata would become too large)
Standardisation: adjustment so that the rates of each factor are adjusted to the proportion of the total population that have that factor e.g. age
Regression: statistical analysis
69
Explain what is meant by public health, and the indicators of health that can be compare
Public Health: science of preventing disease, prolonging life and promoting health through health promotion, protection and services
Indicators: life expectancy and infant mortality
70
Explain what migrant studies have shown about differences in non-infectious disease between populations
NOT genetic and WERE environmental as migrants assume same disease profile as communities they move to, rather than retaining where came from
71
Give examples of common public health campaigns in the UK
Smoking: 15% >18yo smoke, w/unemployed smoking more - smoking cessation programmes to reduce incidence of lung cancer
Obesity: approx 25% obese, w/N-S divide and deprivation - target exercise and diet interventions
Drinking: approx 60% >16yo drink - target harm reduction programmes to reduce crime and chronic disease
72
Give examples of current UK screening programmes
Antenatal: foetal anomalies, infection, SCD
Newborn: physical exam, hearing test and heel-prick test
Adults: cervical cancer (25-64f), AAA (65m)
73
List the advantages of routine data
Advantages:
- Cheap
- Data already collected and in a standardised fashion
- Relatively comprehensive with entire population coverage and/or large sample size
- Wide range of recorded data available for a large number of years
74
List the disadvantages of routine data
Disadvantages:
- May not answer the question (at all or in enough detail)
- Incomplete ascertainment if not every case captured
- Variable quality (e.g. Based on the use of coding / diagnosis)
- Variable validity
- Disease labelling / coding may change over time or by area
75
Identify the current burden of CVD worldwide, and state the main risk factors, with their respective trends
Burden: globally 30% deaths, gradually declining
Risk Factors: hypertension (increases with age in all but isolated populations - INTERSALT), smoking (decline mirrors CVD's) and cholesterol
76
List a generic checklist for critical appraisal
Question, Design, Population, Methods, Analysis, Confounders, Bias, Ethics, Interpretation
77
List and define possible causes for an observed association (and how these may be assessed and rectified)
Chance: normal variation and limited sampling may lead to apparent correlations (look at p-values; increase sample size)
Bias: systematic errors to give incorrect estimate of effect (evaluate design; must be done before study)
Confounding: factors that may have real effect on risk of disease AND factor studied (identify from literature; pseudo-stratification and analysis)
78
List and distinguish different levels of disease prevention and recall examples
Primordial: creating conditions so bad habits never emerge (e.g. sex & rel education to prevent teen pregnancies)
Primary: promotion and specific protection (1:1/screening - e.g. cervical cancer screening)
Secondary: early detection and treatment (e.g. STD testing and treatment to reduce spread)
Tertiary: rehab and damage limitation (e.g. linking MH, acute and community trusts to support alcoholics)
79
List examples of health outcome data routinely collected in the UK
Mortality: death certificates sent to ONS for coding and processing
Cancer: voluntary notification to local registry
Notification of Infectious Disease: reported to LA/health protection team for monitoring
Terminations: must be recorded
Hospital Episode Statistics: cover all NHS using ICD10
QOFs: GP pay per performance - can study care delivered
80
List the Bradford-Hill criteria for establishing causation (9)
Strength: better p-value = more likely causal
Consistency: other studies show same results
Specificity: exposure increases ONE disease
Temporal Rel: exposure MUST precede disease
Dose-Response: increased dose = increased risk
Plausibility: makes biochemical sense
Coherence: cause/effect can't contradict natural history
Experimental evidence: should be available
Analogy: should provide source of hypothesis
81
List the causes for epidemiological transition
\/ Infectious deaths = better sanitation, healthcare and housing
/\ Chronic deaths = smoking, poorer diet, longer life, air pollution, less activity
82
List the commonest infectious causes of world mortality and number of deaths
1. Lower resp - 3.9 mill
2. HIV/AIDS - 2.8 mill
3. Diarrhoeal - 1.8 mill
4. TB - 1.6 mill
5. Malaria 1.2 mill
ITS RAD TB(TO BE) ME
83
What are the underlying causes of high incidence of infectious diseases?
Causes: poor sanitation, low access to healthcare, limited education and crowded living conditions
84
List the commonest non-infectious causes of world mortality and the % deaths globally, and recall causes underlying their high incidence
1) Ischaemic heart disease: narrowing of coronary arteries - 12%
2) Cerebrovascular disease: brain blood vessel disease leading to strokes - 10%
Causes: lack of exercise, hypertension, obesity, smoking, poor diets
85
List the criteria for the disease, test and treatment that must be met to screen for a disease
Disease: important, well-recognised pre-clinical stage, with a long latency period
Test: valid, simple, cheap, reliable, safe and acceptable
Treatment: MUST BE EFFECTIVE AND SAFE - you CANNOT screen for something you can't treat
86
List the indications for screening
Indications:
- early intervention will improve prognosis
- those affected pose risk to others
- identification of high risk individuals can help target interventions
87
List the challenges for screening
Challenges:
- Needs high sensitivity
- May trade off for lower specificity
- If -ve predictive value low, may have more false than true positives
88
List types of routine data
- Healthcare use / outcome data e.g. Deaths/admissions/consultations/prescriptions
- Exposures and Health Determinants e.g. Pollution/crime
- Demographic e.g. Census
- Geographical e.g. Location of health facilities
- Health Service Provision e.g. Staff/bed counts
89
Outline the process of an SR
1) plan using PICOS
2) identify research published using databases, using referenced papers and non-published research
3) select papers meeting criteria
4) Use a meta-analysis to generate a pooled risk estimate, weighing effect size to produce forest plot
5) Report study in meaningful way according to guidelines
90
Outline the steps needed to critically appraise an MA
1) Heterogeneity explored?
2) Publication bias an issue? Affected pooled estimate?
3) Appropriate to pool? homogeneous enough?
4) Appropriate model used?
5) Did different sub-groups give similar results?
HET, BIAS, POOL, MODEL, SUBS
91
Outline the steps needed to critically appraise an SR
1) Clear question? PICOS?
2) Comprehensive? All databases, non-published, independent assessment, appropriate inclusion/exclusion
3) Quality of studies assessed?
4) Credible evidence? high quality studies?
5) Guidelines for reporting
6) Impact on critical practice?
PICOS, COMP, QUALITY, CREDIBLE, GUIDELINES
92
Recall the hierarchy of evidence in study design
```
SR/MA
RCT
Cohort
Case Control
Ecological
Cross-sectional
Case Series
Case Report
Expert opinion
```
"Sarah really couldn't control every crappy confounder causing errors"
93
State the cancers with the largest impact, incidence and mortality
Impact: lung/colorectal and breast/prostate for women/men
Incidence: breast, lung and colorectal
Mortality: lung, liver and stomach
94
What are case reports and how are they used?
Description: Describe a single case - symptoms, history, treatment, response, outcomes
Typical use: inform management of novel/rare disease
95
What are case series and how are they used?
Descritption: Description of several cases
| typical use: inform management of a novel disease
96
What are case controls and how are they used?
Description: Retrospective study with affected and control group representative of population, counting numbers exposed and unexposed to produce an odds ratio
Typical use: studies what causes a rare disease
97
What are cohort studies and how are they used?
Description: Can be retrospective or prospective, taking a cohort of healthy volutneers and recording information about exposure and outcomes to calculate the relative risk
Typical use: Studies impact of risk factors on disease risk
98
What are cross-sectional studies and how are they used?
Description: Uses routine data collected without research in mind to look at presence/absence of disease and exposure at point in time
Typical use: Can compare outcomes in different areas/populations
99
What are ecological studies and how are they used?
Description: Looks at population level associations of disease (CAREFUL OF CONFOUNDERS)
Typical use: Can make geographical comparisons
100
What are expert opinions?
Description: one person's opinion
| Typical use: asking whether your dress looks cool or whether you should change your outfit
101
What are Randomised controlled trials and how are they used?
Description: volunteers meeting inclusion criteria randomly assigned to treatment and placebo groups, with outcomes of each group compared
Typical use:Study effectiveness of drug, treatment or technique
102
What are meta analyses/ systematic reviews and how are they used?
Description: combine and evaluate data and results of many RCTs to see if consensus of trials support studied intervention; meta-analyses combine published estimates to generate a pooled risk estimate
Typical use: Informing guidelines and policy for treatment of patients
103
Using the EER and CER, define relative risk, absolute reduction and relative reduction
Relative risk: EER/CER
Relative reduction: (CER-EER)/CER
Absolute reduction: CER-EER
104
What does a relative risk/ odds ratio of less than 1 mean?
RR: Expect a lower risk
OR: Those with condition are less likely to have been exposed so associated with a reduced risk of disease
105
What does a relative risk/ odds ratio equal to one mean?
RR: expect the same risk
OR: Those with the condition are equally likely to have been exposed so no association with the disease
106
What does a relative risk/odds ratio of greater than one mean?
RR: Expect a higher risk
OR: Those with the condition are more likely to have been exposed so associated with an increased risk of the disease
107
What must be considered for a potential public health intervention
Cost: feasible? screening expensive
Benefit:risk ratio? if individual risk low and intervention carries risk, is it justified?
Ease: can be performed by range of practitioners?
Accessibility: can all access/see?
108
What are the five 'miracle drugs' and what do they treat?
Praziquantel - Schistosomiasis and Tapeworms
Albendazole - Lymphatic Filariasis and intestinal worms
Mebendazole - Intestinal Worms
Mectizan - Onchocerciasis and Lymphatic filariasis
DEC - Lymphatic Filariasis
Zithromycin - Trachoma
109
Define Mass Drug Administration
if small number in population test infected, give drug to everyone without diagnosis
110
What are the requirements for Mass drug administration?
- Safe and effective drugs
- Cheap or donated drugs
- Diagnosis difficult, inaccurate or expensive
111
What are the locations, symptoms and cycle of buruli ulcer?
Location: Ghana/Australia
Symptoms: distinctive Ulcers
Cycle: Mycobacterium Skin disease
112
What are the locations, symptoms and cycle of Chaga's disease?
Location: South America
Symptoms: Fever, diarrhoea and vomiting, splenomegaly then chronic heart problems
Cycle: carried by bed bugs
113
What are the locations symptoms and cycle of Dengue?
Location:globallly increasing
Symptoms: Dengue haemorrhagic fever
Cycle: carried by aeges aegypti
114
What are the location symptoms and cycle of dermal leishmaniasis?
Location: Middle East
Symptoms: wound at bite site
cycle: carried by sandfly
115
What are the locations, symptoms and cycle of leprosy?
Location: Asia, South America and Middle Africa
Symptoms: Granulomas of PNS, eyes and respiratory tracts
Cycle: Mycobacterium skin disease
116
What are the locations symptoms and cycle of podoconiosis?
Location: Africa and South America
Symptoms: swollen feet and legs
Cycle: silicon enters feet
117
What are the locations symptoms and cycle of rabies?
Location: Asia and Africa
Symptoms: foaming and uncontrolled movement (100% mortality)
Cycle: animal reservoirs
118
What are the locations symptoms and cycle of trypanosomiasis?
Location: Africa
Symptoms: Acute Killer or chronic sickness - attacks CNS
Cycle: carried by Tsetse fly
119
What are the locations symptoms and cycle of visceral leishmaniasis?
Location: Asia
Symptoms: fever and weight loss with splenomegaly
Cycle: carried by sandfly
120
What are the NTDs that have no drug treatments?
```
Buruli Ulcer
Chaga's disease
Dengue
Dermal Leishmaniasis
Leprosy
Podoconiosis
Rabies
Trypanosomiasis
Visceral Leishmaniasis
```
121
What are the number of cases, location, symptoms, cycle and treatment of dracunculiasis?
```
No of cases: <30
Location: Africa
Symptoms: burning blister
Cycle: Guinea Worm grow to a metre in leg = scratching blister releases eggs in to water - infection via drinking water
Treatment = slowly extract
```
122
What are the number of cases, locations, symptoms, cycle and treatment of the three types of helminth parasites?
Number of cases: Ascariasis =800m, Trichuriasis =435m, Hookworm=450m
Location: Africa
Symptoms: Stunted Growth
Cycle: Adult worms in lymph nodes - larvae spread by mosquitos
Treatment: Albendazole/Mebendazole
123
What are the number of cases, locations, symptoms, cycle and treatment of lymphatic filariasis?
Number of cases: 120m
location: Africa
Symptoms: Oedema
Cycle: Adult worm in lymph nodes - larvae spread by mosquitos
Treatment: Albedazole/Mectizan(Africa)/DEC(Asia) - Albedazole treatment is funded by GSK - 1bn per year
124
What are the number of cases, locations, symptoms, cycle and treatment of Onchocerciasis?
```
Number of Cases: 15m
Location: West Africa Rivers
Symptoms: Bilateral Vision Loss
Cycle: Worm in nodules under the skin - larvae transferred by blackfly
Treatment: Mectizan
```
125
What are the number of cases, locations, symptoms, cycle and treatment of Schistosomiasis?
```
Number of cases: 200m
Location: Rural Africa
Symptoms: Fibrosis
Cycle:Eggs in blood, Larvae in urine, infect snails and reproduce, release to water, penetrate skin
Treatment: Praziquantel
```
126
What are the number of cases, locations, symptoms, cycle and treatment of Trachoma?
```
Number of Cases: 84m
Location:Africa
Symptoms: Conjunctivitis and Blindess
Cycle: Flies and transfer of eye secretions
Treatment: Azithromycin
```
