Human African Trypanosomiasis: Sleeping Sickness in Sub-Saharan

Africa

Matthew Malone

3/9/2012

Learning Goals

•  Understand the causes, risk factors, and modes of transmission for Human African Trypanosomiasis (HAT)

•  Know the role of armed conflict in the rise of infection rates

throughout Africa

•  Use past HAT outbreak patterns and causes to understand the implications for future infection

The Problem

•  Multiple HAT outbreaks have occurred over the last century.

•  Armed conflict in Africa has escalated disease rates in recent years.

•  Continued displacement of populations may cause many more outbreaks.

•  Displacement widens the geographic disease spread.

Causal Agents

•  Caused by the protozoan Trypanosoma Brucei

•  Has three subspecies: –  Trypanosoma brucei

gambiense –  Trypanosoma brucei

rhodesiense –  Trypanosoma brucei

brucei (animals only)

Vector Biology

•  The vector for HAT is the tsetse fly

•  Biological Vector •  Inhabits rural areas •  Bites during daytime hours •  Both males and females are

capable of carrying and transmitting the disease.

Vector Biology Cont’d

•  Tsetse flies belong to the genus Glossina

•  Glossina contains 3 subgroups –  Glossina (includes G.

morsitans group) –  Nemorhina (includes G.

palpalis group) –  Austenina (includes G.

fusca group)

Vector Biology Cont’d

•  Vectors of T.b. gambiense –  G. palpalis & G.

tachinoides groups

•  Vectors of T.b. rhodesiense –  G. morsitans, G.

swynnertoni, & G. pallidipes groups

EPIDEMIOLOGY AND CONTROL OF HUMAN AFRICAN TRYPANOSOMIASlS 95

karyotype. Their identification used to be based on Pollock's scheme (1982), after dissection and microscopical examination. Recently, software has been developed for the specific and subspecific identification of glossinids and the determination of their epidemiological importance (Brunhes, 1994).

The vectorial capacity of a species of Glossina is determined by its ability to become infected while feeding on a vertebrate host, and subsequently to support the development of the infection and to transmit the trypanosome to another vertebrate host (Challier, 1982). According to these criteria, only the G. palpal is and G. morsi tans groups contain species and subspecies that are vec- tors of T. b. gambiense (Table 1). The G. palpal is group contains two excellent vector species of T. b. gambiense and of animal trypanosomiases in West and Central Africa: G. palpal is palpal is in forest areas and G. p. gambiens is in savannah areas. In West Africa, biometric studies of the male and female geni- talia of G. p. palpal is and G. p. gambiensis , carried out on samples captured along four north-south lines, has delineated the geographical boundary between the two subspecies: the former inhabits the forest areas and the moist savannah, whereas the latter is found in the semi-arid savannah (Nekpeni et al., 1989). In the forest belt of C6te d'Ivoire, where several species cohabit, G. p. palpal is is the only vector of the human disease and outnumbers other species

Table 1 Species and subspecies of the two subgenera of Glossina which are vectors of T. b. gambiense and T. b. rhodesiense.

Subgenus (group) Species Subspecies

Nemorhina (palpalis) G. palpalis a G. p. palpalis a G. p. gambiensis a

G. fuscipes a'b G. f fuscipes a,b G. f martinii G. f quanzensis G. p. pallicera G. p. newsteadi

Glossina ( mo rsitans )

G. pallicera

G. tachinoides a G. caliginea

G. morsitans b

G. swynnertoni b G. longipalpis G. pallidipes b G. austeni

G. m. morsitans b G. m. submorsitans G. m. centralis b

a Vector of T. b. gambiense. b Vector of T. b. rhodesiense.

Reservoirs

T.b. gambiense T.b. rhodesiense

PLoS Medicine | www.plosmedicine.org 0177 February 2008 | Volume 5 | Issue 2 | e55

Health Assembly called on member states to sustain the effort to eliminate the disease as a public health problem, which led the WHO programme to intensify its coordinating efforts, bringing together national control programmes, non-governmental organisations, research institutions, and other concerned United Nations Agencies (under the Programme against African Trypanosomiasis, PAAT) [5], as well as private and public contributors (Sanofi-Aventis, Bayer HealthCare, the Bill & Melinda Gates Foundation, and the Belgium and French Cooperation). With this broad coalition, field activities were scaled up, leading to better knowledge of the disease distribution and a reduction in new cases by 2006, as described above. The current prevalence and incidence figures are believed to reflect the overall situation quite accurately, in contrast with the uncertainties surrounding the figures prior to 1997.

Given that in 2006, 20 out of 36 endemic countries achieved or were close to achieving the target of reporting no new cases, and eight countries reported less than 100 new

cases per year, elimination has become a feasible objective in many countries endemic for HAT. With elimination in mind, in May 2007 WHO organised an Informal Consultation on Sustainable Sleeping Sickness Control, during which endemic country representatives debated the current disease landscape and concluded that elimination was possible.

Political will. During the July 2000 Organization of African Unity (now the African Union) summit held in Lomé, Togo, the African Heads of State and Government adopted the decision to collectively embark on a Pan African Tsetse and Trypanosomosis Eradication Campaign (PATTEC). This campaign was based on the realisation that (1) solving the tsetse fly and disease problem would be an important contribution to Africa’s development, and (2) this could not be done by a single country acting alone. A task force of African experts concluded that such a campaign was not only technically feasible, but economically productive [6].

Implementation is on its way; six countries have recently received financial support from the African Development

doi:10.1371/journal.pmed.0050055.g002

Figure 2. HAT Transmission CycleIn T. b. gambiense, the cycle is mostly human-to-human (central circle); occasionally transmission may occur from animal to human. In T. b. rhodesiense,the animal reservoir plays an important role in the cycle, thus sustaining parasite transmission and human infections.

Table 2. T. b. rhodesiense Sleeping Sickness: New Cases Reported between 1997 and 2006Countries 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

More than 100 but less than 1,000 new cases per yearTanzania 354 299 288 347 258 226 111 157 183 125Uganda 217 283 283 266 426 328 321 318 479 245

Less than 100 new cases per yearMalawi 7 10 11 35 38 43 70 47 41 58Zambia nd nd 15 9 6 17 7 35 20 57

Sporadic new casesKenya 5 14 22 12 14 13 0 0 0 1Mozambique nd nd nd nd nd 1 nd 1 nd ndRwanda nd nd nd nd 8 27 5 22 nd ndZimbabwe 9 nd nd nd nd nd nd nd 4 nd

No new casesBotswana nd nd nd nd nd nd nd nd nd ndBurundi nd nd nd nd nd nd nd nd nd ndEthiopia nd nd nd nd nd nd nd nd nd ndNamibia nd nd nd nd nd nd nd nd nd ndSwaziland nd nd nd nd nd nd nd nd nd ndTotal 592 606 619 669 750 655 514 580 727 486

nd, no data reporteddoi:10.1371/journal.pmed.0050055.t002

Transmission Cycle

Risk Factors

•  Civil Disturbance/War •  Cattle Movements •  Population Movements/

Migrations (Refugees) •  Reduced Health

Program Financing •  Rural Living

Environment

Case Study: Uganda HAT Outbreak

•  Began in the late 1980s and persisted through 2005

•  Refugees migrated from Uganda to Zaire and Sudanàacquired infection

•  Refugees migrated back to Uganda accompanied by infected Sudanese refugeesàspread infection

Case Study Cont’d

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Epidemiology

•  In 1986, it was estimated that approx. 70 million people lived in areas conducive to disease transmission

•  HAT affects 36 countries in sub-Saharan Africa

•  According to the World Health Organization, HAT causes ~40,000 deaths in Africa annually

Epidemiology Cont’d

•  The total amount of reported HAT cases has decreased substantially over time.

•  1998: ~40,000 reported cases; >250,000 actual cases

•  2004: ~18,000 reported cases; between 50,000 and 70,000 actual cases

•  2010: ~7,000 reported cases; ~30,000 actual cases •  Cases involving T.b. rhodesiense are much rarer than

those involving T.b. gambiense.

Epidemiology Cont’d

Seminar

150 www.thelancet.com Vol 375 January 9, 2010

Trypanosomes are surrounded by a surface coat composed of a variant surface glycoprotein that protects them from lytic factors in human plasma.39 When infection occurs, this glycoprotein is recognised by the host’s immune system, which starts producing IgM and IgG antibodies. These antibodies neutralise the corresponding trypanosomes, leading to a decrease of parasitaemia. However, a few of the trypanosomes will have changed their surface coats to a new variant surface glycoprotein type that is not aff ected by the circulating antibodies, so that they can continue to proliferate until new antibodies are produced. This sequence continues, and the immune system is not able to eliminate the parasites. About 2000 variant surface glycoprotein genes, including many pseudogenes, are present in the genome of T brucei,40,41 whereas T b gambiense probably has fewer. Only one such glycoprotein is expressed at a specifi c time. The switch occurs either by transport of a variant surface glycoprotein gene to one of 20 expression sites situated on diff erent telomeres, or by silencing of an active telomere and activation of a telomere on another chromosome. Because of this high degree of antigenic variation, development of a vaccine is unlikely to be feasible.42

Domestic and wild animals can also become infected with T b gambiense43 and T b rhodesiense. Although they do not fall ill, they have an epidemiological role as carriers or reservoir animals from which tsetse fl ies can acquire an infection.44 For T b rhodesiense, which is a zoonosis that is usually transmitted from animals to man, cattle are an important reservoir,45,46 although most wild animals species in game parks can harbour human-pathogenic trypanosomes. For T b gambiense, which is anthro-ponotic—ie, it mostly depends on human-to-human transmission—man provides the main reservoir. Animals play a less important part, but pigs and some wild animal species have been reported as being a reservoir.47,43

Clinical features The disease appears in two stages, the fi rst haemolymphatic stage and the second meningo-encephalitic stage, which is characterised by invasion of the CNS. The penetration of trypanosomes through the blood-brain barrier is an active process48 and occurs at or near intracellular junctions. Disease caused by either of the two parasites leads to coma and death if left untreated. T b gambiense infection is characterised by a chronic progressive course. According to models based on survival analysis, the estimated average duration of such infection is around 3 years, which is evenly divided between the fi rst and second stages.49 T b rhodesiense disease is usually acute, and death occurs within weeks or months.50

A trypanosomal chancre (a reaction at the location of the tsetse fl y bite) is rarely seen with T b gambiense, but occurs in 19% of patients infected with T b rhodesiense. The leading signs and symptoms of the fi rst stage are chronic and intermittent fever, headache, pruritus, lymphadenopathy, and, to a lesser extent, hepatospleno-megaly. In the second stage, sleep disturbances and neuro-psychiatric disorders dominate the clinical presentation.

Fever is intermittent, with attacks lasting from a day to a week, separated by intervals of a few days to a month or longer,51 and is rarely seen in the second stage.52 The febrile episodes correspond to a type 1 infl ammatory reaction associated with activation of macrophage-1 cells and high concentrations of interferon γ, tumour necrosis factor, reactive oxygen intermediates or metabolites, and nitric oxide. This reaction controls parasite invasion and proliferation, but the exacerbated immune response can induce collateral tissue damage.53 To alleviate parasite-elicited pathological changes the host can mount type 2 immune responses consisting of sequential production of interleukin 10 and interleukin 4 or interleukin 1 that can induce macrophage-2 cells with anti-infl ammatory

Figure !: Trypanosoma brucei gambiense: comparison between population placed under active surveillance and new casesNumber of reported cases (columns) and population screened (circles), Africa, 1939–2004. Reproduced under the creative commons licence from reference 6.

Population screened (!106)N

umbe

r of c

ases

(!10

4 )

19391944

19491954

19591964

19691974

19791984

19891994

19992004

0

1

2

3

4

5

6

7

8Population screenedReported cases

6

5

4

3

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Year

Geographical Distribution

•  1998- World Health Organization states that there are over 200 active foci of HAT between latitude 15 degrees north and 15 degrees south (“tsetse belt”).

•  T.b. gambiense is mostly found in western and central Africa. –  Over 95% of the cases of human infection found in the

Democratic Republic of Congo, Angola, Sudan, Central African Republic, Chad, and northern Uganda.

•  T.b. rhodesiense is found mostly in eastern and southern Africa. –  Over 95% of the cases of human infection occur in

Tanzania, Uganda, Malawi, and Zambia.

Geographical Distribution Cont’d

PLoS Medicine | www.plosmedicine.org 0178 February 2008 | Volume 5 | Issue 2 | e55

Bank and have initiated the first phase of a PATTEC project. In addition, four countries in the Kwando/Zambezi region have begun PATTEC activities, with very encouraging results.

The Next StepsIntegration of activities. The challenge for the immediate future is to avoid repeating past mistakes, and to achieve cost-effective, sustainable HAT surveillance and control. Sustainability can only be achieved through an integration of activities in a strengthened health system able to face such responsibilities. The current approach should include specialised teams and health care systems, rather than falling back on the former debate between the value of specialised teams or primary health care. In other words, specialised teams and primary health care need to work together synergistically [7].

But integration is not a simple delegation process. Major responsibilities cannot simply be passed on to the existing health services of remote rural areas inappropriately trained and equipped to handle HAT control. Integration must mean the active participation of a strengthened health system capable of implementing surveillance and control activities, buttressed by specialised HAT national staff. Unfortunately, the existing tools limit the full participation of the health care system staff in controlling the disease. The two main technical bottlenecks are the lack of a sensitive and specific diagnostic test and of a new drug that is cheap, safe, and easy to administer.

New approaches to surveillance and control. To sustain recent achievements in HAT control and the epidemiological downward trend, it will be necessary to develop a novel approach for surveillance and control adapted to the new requirements. This approach consists of an integration process involving national health care systems. Implementation, however, will require better tools than those presently available for diagnosis and treatment. Such a health systems–based approach may be adequate for areas affected

by T. b. gambiense, but in areas affected by T. b. rhodesiense,disease control cannot rely exclusively on human health services and will have to involve veterinary and entomological services as well.

Developing new diagnostic tools. Attempts to identify new antigens should result in more specific and sensitive tests for serodiagnosis of the disease, while changes in test format (i.e., the development of non-invasive saliva tests [8]) should result in more user-friendly tests. Much progress has been made in the development of molecular tools. Specific genes for both T. b. gambiense and T. b. rhodesiense have been identified [9–11] for PCR-based detection of infection. Molecular dipstick tests allow easier reading of the PCR result [12], and the first results using loop-mediated isothermal amplification [13] are encouraging.

Disease bio-markers are being investigated using proteomics, such as surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-ToF-MS) [14]. However, these newly developed techniques, claimed to be substantially more sensitive and specific than those available in the field today, often rely on complicated equipment. As a result, the test protocols are not compatible with prevailing conditions at HAT treatment centres in rural Africa. WHO has established a collaboration with the Foundation for Innovative New Diagnostics (http://www.finddiagnostics.org/) to develop new simple diagnostic tools for the control of HAT that meet the requirements of a sustainable elimination approach. The desired characteristics of a new test were defined as being “ready for use”, stable at room temperature, and affordable by national health systems. The new test should provide an uncontroversial diagnosis of both forms of the disease and require minimum training and equipment to allow its execution by any health worker.

Developing new tools for determining stage of disease. Aslong as there is no safe and effective drug available to treat both stages of the disease, determining disease stage will remain necessary. Some progress has been made through the development of a point-of-care card agglutination test for immunoglobulin M quantification in cerebrospinal fluid [15]. Although this test appears highly promising in establishing central nervous system involvement, its accuracy and feasibility in the field still need to be ascertained. The study of anti-neurofilament and anti-galactocerebrosides antibodies [16] may open new avenues for staging the disease. Unfortunately, all these techniques continue to require a lumbar puncture. Stage markers in other body fluids such as serum, urine, or saliva could become ideal tests to avoid the invasive procedure of a lumbar puncture, but remain to be identified.

Another possible technique for the diagnosis of central nervous system involvement is the measurement of sleep-onset rapid eye movement by polysomnography, a method that involves assessing the sleep pattern of patients [17]. However, although it is not invasive, polysomnography has not yet been proven to be universally accurate. Obviously, much work still needs to be done to make improved staging tests available to health workers in endemic areas.

Advances in drug development. Eflornithine was developed over 20 years ago, and was registered for the treatment of gambiense disease in 1990. While the drug is safer than melarsoprol [18], eflornithine does have side effects: fever, unusual bleeding and weakness, diarrhoea, nausea, stomach

doi:10.1371/journal.pmed.0050055.g003

Figure 3. Map of Africa Showing the Epidemiological Status of Countries Considered Endemic for the Disease

Geographical Distribution/Conflict

•  The resurgence of HAT in several countries has been attributed to conflict and/or war.

•  Cases of HAT have been seen to occur significantly more often in countries where there is conflict, internationalized civil war, and/or high political terror.

Geographical Distribution/Conflict Cont’d

by other processes associated with both conflict and public health,including education, democracy, and health expenditures (Hoddie& Smith, 2009; Li & Wen, 2005). Pooling of data and national-level confounders are to some extent accounted for in regressionmodel results through the integration of a robust standard errorsestimation, which considers clustering of observations by country.

The analyses do not account for selection bias due to reducedsurveillance during times of conflict or violence (Murray et al.,2002). Similarly, incidence data provide only a proxy measureand do not necessarily reflect total burden in a given year since onlynew cases are represented and existing chronic cases e contrib-uting to both prevalence and the parasite reservoir e are notaccounted for. Surveillance data could not be integrated into anal-yses due to an absence of sufficient data for all countries and years.Sub-set analyses, however, revealed that the relationship betweenHAT incidence and screening is complex. In some countries, therewas a significant positive relationship between screening andincidence, while in others there was a significant negative rela-tionship. This inconsistency can be explained by the occurrence oftwo processes relating surveillance to case reporting. First, thenumber of reported cases is expected to rise with an increasingnumber of people screened as actual cases are detected and under-detection is reduced. Second, and conversely, an increase in thenumber of people screened can be expected to provide increasedopportunity for case treatment and reduced transmission, thusreducing the number of cases reported. It is difficult to disentanglethese two processes given existing data, and results are unlikely tobe translatable to T.b. rhodesiense regions where animals areimportant reservoirs of disease, and vector control rather thansurveillance is considered the primary intervention for trans-mission. Given that surveillance is in some cases a response to thecommencement of an outbreak, controlling for populationscreening may actually over-control for real incidence. We thuschose not to attempt to control for screening due to the potentialfor reverse causality; HAT incidence may in some cases triggerincreased surveillance, thus creating the potential for over-controlin the model. Côte d’Ivoire, for example, had a resurgence of casesin the early 2000s, associated with socio-political disruptions andan influx of Sudan refugees during the Sudanese civil war in the1990s; case data for that country and period show a dramatic dropin incidence which more likely reflects reduced surveillance (Kabaet al., 2006). A lack of clear integration of reporting errors will biasdata and results, though this is likely to bias results towards the nulldue to reduced surveillance during periods of conflict.

Given the focal nature of HAT incidence, using sub-national datato provide increased statistical power would allow more detailedanalysis of country-specific models and inter-country comparisons.There are insufficient observations to provide statistical power forindividual country modeling, but there are certainly differencesbetween countries which are not captured in the pooled data anal-yses presented here. Recent prioritization and current initiatives tocollect spatially-explicit, harmonized, and fine resolution baselinedata of HAT incidence will significantly contribute to improved,multi-scale analyses of the determinants of HAT across and withincountries (Cattand, Jannin, & Lucas, 2001; Cecchi et al., 2009; WHO,2005). The appropriateness of downscaled conflict data is, however,less clear, given that the indirect health effects of conflict likelyoccurat thenational or regional scalee researchon conflict andhealthhasbeen dominated by national-level analyses. Recent initiatives incrisis mapping (e.g. http://hhi.harvard.edu) provide new opportu-nities for downscaled, rapid spatial surveillance of conflict events.Difficulties in reconciling spatial and temporal modeling of conflictas a determinant of HAT is complicated by the dichotomy betweenthe scales at which the two variables are appropriately measuredand across which they vary; combined with the challenge of quan-tifying conflict measures, this provides a barrier to integration ofsocial determinants of incidence with quantitative research andpolicy prioritizations. Use of national data limits the interpretivepower of the results, which cannot be extrapolated to local occur-rence of conflict and HAT incidence. The data used here are notappropriate for direct causal inference. The results are, however,

Fig. 3. aeb: HAT incidence by a) conflict severity, and b) Political Terror Scale level.Error bars are not shown since data are highly over-dispersed/non-parametric. PoliticalTerror Scale based on US State Department data (Gibney et al., 2009).

Fig. 4. Descriptive analysis summary of HAT incidence by conflict and terror cate-gories. Inter-state and territorial conflict are excluded due to low observation counts.Error bars are not shown since data are highly over-dispersed/non-parametric.

L. Berrang-Ford et al. / Social Science & Medicine 72 (2011) 398e407404

by other processes associated with both conflict and public health,including education, democracy, and health expenditures (Hoddie& Smith, 2009; Li & Wen, 2005). Pooling of data and national-level confounders are to some extent accounted for in regressionmodel results through the integration of a robust standard errorsestimation, which considers clustering of observations by country.

The analyses do not account for selection bias due to reducedsurveillance during times of conflict or violence (Murray et al.,2002). Similarly, incidence data provide only a proxy measureand do not necessarily reflect total burden in a given year since onlynew cases are represented and existing chronic cases e contrib-uting to both prevalence and the parasite reservoir e are notaccounted for. Surveillance data could not be integrated into anal-yses due to an absence of sufficient data for all countries and years.Sub-set analyses, however, revealed that the relationship betweenHAT incidence and screening is complex. In some countries, therewas a significant positive relationship between screening andincidence, while in others there was a significant negative rela-tionship. This inconsistency can be explained by the occurrence oftwo processes relating surveillance to case reporting. First, thenumber of reported cases is expected to rise with an increasingnumber of people screened as actual cases are detected and under-detection is reduced. Second, and conversely, an increase in thenumber of people screened can be expected to provide increasedopportunity for case treatment and reduced transmission, thusreducing the number of cases reported. It is difficult to disentanglethese two processes given existing data, and results are unlikely tobe translatable to T.b. rhodesiense regions where animals areimportant reservoirs of disease, and vector control rather thansurveillance is considered the primary intervention for trans-mission. Given that surveillance is in some cases a response to thecommencement of an outbreak, controlling for populationscreening may actually over-control for real incidence. We thuschose not to attempt to control for screening due to the potentialfor reverse causality; HAT incidence may in some cases triggerincreased surveillance, thus creating the potential for over-controlin the model. Côte d’Ivoire, for example, had a resurgence of casesin the early 2000s, associated with socio-political disruptions andan influx of Sudan refugees during the Sudanese civil war in the1990s; case data for that country and period show a dramatic dropin incidence which more likely reflects reduced surveillance (Kabaet al., 2006). A lack of clear integration of reporting errors will biasdata and results, though this is likely to bias results towards the nulldue to reduced surveillance during periods of conflict.

Given the focal nature of HAT incidence, using sub-national datato provide increased statistical power would allow more detailedanalysis of country-specific models and inter-country comparisons.There are insufficient observations to provide statistical power forindividual country modeling, but there are certainly differencesbetween countries which are not captured in the pooled data anal-yses presented here. Recent prioritization and current initiatives tocollect spatially-explicit, harmonized, and fine resolution baselinedata of HAT incidence will significantly contribute to improved,multi-scale analyses of the determinants of HAT across and withincountries (Cattand, Jannin, & Lucas, 2001; Cecchi et al., 2009; WHO,2005). The appropriateness of downscaled conflict data is, however,less clear, given that the indirect health effects of conflict likelyoccurat thenational or regional scalee researchon conflict andhealthhasbeen dominated by national-level analyses. Recent initiatives incrisis mapping (e.g. http://hhi.harvard.edu) provide new opportu-nities for downscaled, rapid spatial surveillance of conflict events.Difficulties in reconciling spatial and temporal modeling of conflictas a determinant of HAT is complicated by the dichotomy betweenthe scales at which the two variables are appropriately measuredand across which they vary; combined with the challenge of quan-tifying conflict measures, this provides a barrier to integration ofsocial determinants of incidence with quantitative research andpolicy prioritizations. Use of national data limits the interpretivepower of the results, which cannot be extrapolated to local occur-rence of conflict and HAT incidence. The data used here are notappropriate for direct causal inference. The results are, however,

Fig. 3. aeb: HAT incidence by a) conflict severity, and b) Political Terror Scale level.Error bars are not shown since data are highly over-dispersed/non-parametric. PoliticalTerror Scale based on US State Department data (Gibney et al., 2009).

Fig. 4. Descriptive analysis summary of HAT incidence by conflict and terror cate-gories. Inter-state and territorial conflict are excluded due to low observation counts.Error bars are not shown since data are highly over-dispersed/non-parametric.

L. Berrang-Ford et al. / Social Science & Medicine 72 (2011) 398e407404

Geographical Distribution/Conflict Cont’d

•  Forced population movement increases transmission.

•  Migration causes trypanosomes to circulate from high-incidence to low-incidence areas.

•  Conflict causes breakdown of control measures and surveillance, increasing disease spread

References

1. Pepin J., Meda H. The epidemiology and control of human African trypanosomiasis. Adv Parasitol, 49 (2001), pp. 71–132 2. Human African trypanosomiasis (sleeping sickness). Available at http://www.who.int/mediacentre/factsheets/fs259/en/. Accessed March 8, 2012. 3. Smith D., Pepin J., Stich A. Human African trypanosomiasis: an emerging public health crisis. Br Med Bull, 54 (1998), pp. 341–355 4. Brun R., Blum J., Chappuis F., Burri C. Human African trypanosomiasis. Lancet (2009), pp. 148–159 5. Simarro P., Jannin J., Cattand P. Eliminating human African trypanosomiasis: where do we stand and what comes next? PLoS Med. 5, e55 (2008), pp. 174–180

References Cont’d

6. Parasites- African Trypanosomiasis (also known as Sleeping Sickness). Available at http://www.cdc.gov/parasites/sleepingsickness/. Accessed March 8, 2012. 7. Berrang-Ford L, Martin O, Maiso F, Waltner-Toews D, McDermott J (2006) Sleeping sickness in Uganda: revisiting current and historical distributions. Afr Health Sci 6: 223–231 8. Kuzoe FAS. (1993) Current situation of African trypanosomiasis. Acta Trop. 54: 153-162 9. MacGregor P., Matthews K. New discoveries in the transmission biology of sleeping sickness parasites: applying the basics. J. Mol. Med., 88 (2010), pp. 865–871

References Cont’d

10. Berrang-Ford L., Breau L. Conflict and human trypanosomiasis. Soc. Sci. Med. (2010), pp. 398–407