Demographic data of the sample population.
\r\n\t[2] J. V. Moloney, A. C. Newell. Nonlinear Optics. Westview Press, Oxford, 2004.
\r\n\t[3] M. Kauranen, A. V. Zayats. Nonlinear Plasmonics. Nature Photonics, vol. 6, 2012, pp. 737-748.
\r\n\t[4] P. Dombi, Z. Pápa, J. Vogelsang et al. Strong-field nano-optics. Reviews of Modern Physics, vol. 92, 2020, pp. 025003-1 – 025003-66.
\r\n\t[5] N. C. Panoiu, W. E. I. Sha, D.Y. Lei, G.-C. Li. Nonlinear optics in plasmonic nanostructures. Journal of Optics, 20, 2018, pp. 1-36.
\r\n\t[6] A. Krasnok, A. Alu. Active nanophotonics. Proceedings of IEEE, vol. 108, 2020, pp. 628-654.
\r\n\t[7] M. Lapine, I.V. Shadrivov, Yu. S. Kivshar. Colloquium: Nonlinear metamaterials. Reviews of Modern Physics, vol. 86, 2014, pp. 1093-1123.
\r\n\t[8] Iam Choon Khoo. Nonlinear optics, active plasmonics and metamaterials with liquid crystals. Progress in Quantum Electronics, vol. 38, 2014, pp. 77- 117.
\r\n\t
Around the world, resident hunting as part which is generally organized and managed by the state as a public service [1] has proven to be a powerful tool to promote conservation when conducted in ways that are biologically sound within appropriate governance and institutional settings [2]. License fees and taxes are set and taken by the state and in most situations are reinvested in managing the resource. In developing countries apart from conservation, public hunting can be regarded as a source of income as well as a livelihood strategy in terms of food security and in combating malnutrition. On the other hand, public hunting model has not worked effectively for conservation in Africa and other developing regions such as Central Asia and even Mexico [3]. For example, governance, accountability mechanisms, and state agencies are unable to capture and channel license or tax revenues to manage and support conservation programs as they do in the North American Model [3].
\nIn Tanzania resident hunting is recognized by the wildlife policy [4] which states that it is the right of indigenous Tanzanians to have legal access to wildlife use, and different scales of fees for tourists and residents to hunt have been established through the enabling legislation. The country has over 140 hunting concessions covering an area in excess of 250,000 km2 that are licensed to conduct both tourist hunting and resident hunting. These concessions are distributed throughout the country in either Game Reserves and Game Controlled Areas, open areas, or Wildlife Management Areas. Schedules of the Hunting Regulations that support the Wildlife Conservation Act specify types of animals that may or may not be hunted on a hunting license. A wide range of animals (approximately 60 species) can legally be hunted by tourist hunters in Tanzania. However, the giraffe, cheetah, rhino, and wild dog are protected game and cannot be hunted in Tanzania. The Hunting Regulations stipulate the fees for hunting every type of animal and further specify a minimum number of hunting days. Currently there are over 40 hunting outfitters leasing concessions in Tanzania.
\nIn Serengeti District before the 2002 joint venture between Serengeti District Council (SDC) and Singita Grumeti Reserve Limited (SGRL) which banned resident hunting, the latter was undertaken using existing regulations. Resident hunting was formally carried out in Nyichoka and Sibora open areas of Serengeti District. The chapter assesses the implications of the hunting ban on local communities’ livelihood and examines the wildlife population trend after the ban.
\nSerengeti District (10,373 km2) is located on the Eastern part of Mara region (Figure 1). The district has 10 wildlife areas, viz., Serengeti National Park (7000 km2), Grumeti Game Reserve (68.37 km2), Ikorongo Game Reserve (189.68 km2), IKONA Wildlife Management Area (WMA) (148 km2), and open areas—IKONA Open Area, Issenye Open Area, Issenye Reminder, Nyakitono Reminder, Robanda Open Area, and Sasakwa, having a total of 2306 km2. About 659 km2 is the area for agriculture, livestock keeping, and for settlements.
\nLocation of the study area.
Average rainfall in the area is about 700 mm per annum. The temperatures in the area show a relatively constant mean monthly maximum of 27–28°C. The minimum temperature varies from 16°C in the hot month of October–March to 13°C during May–August. The relief ranges from 1144 to 1380 m above sea level.
\nThis study involved three communities of Natta Mbiso, Machochwe, and Park Nyigoti. The criteria for picking these communities were their traditional link to wildlife utilization and adjacency to former hunting areas and/or protected area networks in the district. As for game population, emphasis was on IKONA WMA, which entered an agreement with Singita Grumeti Reserve Limited (SGRL).
\nSGRL under a multi-billionaire businessman Paul Tudor II was registered in 2002 and has tourism right tenure over the Grumeti Game Reserve, Ikorongo Game Reserve, and Ikoma Wildlife Management Area. The SGRL which is one of the most ambitious conservation and tourism projects in Africa is a private game concession and has excellent year-round game viewing and is also ideally placed for annual wildebeest migration. Currently SGRL project operates three 7-star tourist lodges in the area: the Sasakwa Hilltop, Sabora plains, and Faru Faru River lodges with a total of 72 beds. The vision of SGRL is rehabilitation and maintenance of the indigenous biodiversity of the western Serengeti-Mara ecosystem for the benefit of the local communities within the Serengeti District and the nation as a whole through structures that are financially and economically sustainable, ecologically and environmentally responsible, and politically acceptable.
\nFrom 2003 to 2011 the company had invested a huge sum of money into lodges, community development, and environmental projects in Serengeti and Bunda Districts. Out of this funding, 2.8 and 2.3% have been used for community development projects and wildlife management activities, respectively. Among the community development projects include President Kikwete scholarships, provision of clean and safe water, education, and beekeeping projects.
\nIn 2002 SGRL project entered a joint venture agreement with Serengeti District Council (SDC) on resident hunting ban, and Clause 4.1.6 of the contract states that: “SGRL shall compensate the District Council a sum of TZS 200 Million only for the community development quota allocated to the District Council. The amount will be allocated in a transparent and accountable manner involving all stakeholders in the Serengeti District” (JVA, Pp. 12).
\nHowever, SGRL continues with tourist hunting in the former hunting areas incongruent to the joint venture agreement.
\nData involving humans were collected using household questionnaire and structured interviews. The main subjects were households, district officials, and village leaders. Using the village register book, a sample of 30–35 households was picked using simple random sampling technique. Gender balance was considered in picking the household sample. The sample was approximately 7–9% of the village population and can be argued to be an appropriate sample for the study. A total of 100 household respondents were interviewed. As for District officials, officials involved were the District Natural Resources Officer (DNRO) and District Game Officer (DGO). At village level, Village Executive Officers from the three villages were the main respondents. Socioeconomic data were analyzed using SPSS version 16, and this was supplemented with qualitative data analysis techniques such as content analysis and memoing.
\nBetween August 16 and August 21 of 2010, the survey of wildlife (large mammals) was undertaken in the census area (data presented are for IKONA WMA). During game census, the census was preceded by a generally above-average wet season rain. The 2 months prior to the census were, however, well below average. No rain was recorded in August and none fell during the census.
\nTemperatures were generally moderate to warm. Three methods were applied to estimate wildlife populations in IKONA WMA. These include (i) “known groups” method, (ii) total area aerial counts, and (iii) sample aerial counts. In the “known group method,” an attempt was made to count all groups and individuals in the population by individual and group recognition. This was only suitable for the rarer species, and so far, it was only attempted for the roan antelope.
\nFor aerial counts using a helicopter (90 m above ground), two forms of aerial counts were implemented simultaneously, namely, total area count and sample estimate based on distance sampling principles [5]. The techniques were implemented following the standard procedures as described by [6]. The air speed was between 40 and 60 knots. Transects were flown morning and afternoon, up to maximum of 3 hours. The hottest part of the day was avoided, as animals tended to rest under the shade at this time and as a consequence are more difficult to spot. Data analysis also followed standard procedures [6].
\nOn average the majority of the respondents were female which formed 46% (N = 100) except in Natta Mbiso where the majority were males (Table 1). As for age about 74% were aged between 18 and 45 years implying that the majority of the sample populations were youths and therefore an economically active workforce. At specific village level, Machochwe and Natta Mbiso had the highest proportion of youths with 82 and 77%, respectively. In terms of education, the majority (72%) had attained primary school education, 9% have not been to school, and 19% had secondary school education and above. Of the three villages, Natta Mbiso had the highest proportion of people with secondary education. This could be attributed to its strategic location as it is along the Musoma-Arusha main road and the village’s sub-township nature compared to the remaining two villages.
\nVillage | \nN | \nSex (%) | \nAge (%) | \nEducation (%) | \n||||||
---|---|---|---|---|---|---|---|---|---|---|
M | \nF | \n18–25 | \n26–35 | \n36–45 | \n>45 | \nInf. | \nPry | \nSec | \n||
Park Nyigoti | \n35 | \n47.4 | \n52.6 | \n31.6 | \n10.5 | \n21.1 | \n36.9 | \n15.8 | \n68.4 | \n15.8 | \n
Natta Mbiso | \n30 | \n54.5 | \n45.5 | \n27.3 | \n13.6 | \n36.4 | \n22.7 | \n0 | \n63.6 | \n36.4 | \n
Machochwe | \n35 | \n35.5 | \n64.5 | \n17.6 | \n23.5 | \n41.2 | \n17.6 | \n11.8 | \n82.4 | \n5.8 | \n
Average | \n33.3 | \n45.8 | \n54.2 | \n25.5 | \n15.9 | \n32.9 | \n25.7 | \n9.2 | \n71.5 | \n19.3 | \n
Demographic data of the sample population.
On average 95% of household respondents in the three villages were aware of the ban (Figure 2). The high awareness could probably be attributed to the fact that these communities have for a long time been linked to bush meat hunting and/or consuming. The fact that they are no longer enjoying access to bush meat as it used to be has probably made them to be aware of the ban. On whether they were involved in meetings and/or discussions before implementing the ban, 95% argued that they were not involved at all, and the remaining proportion were not sure.
\nAwareness on hunting ban.
However, the District Natural Resources Officer (DNRO) and District Game Officer (DGO), when asked about community involvement, both argued that the decision was reached through the Serengeti District Full Council, and therefore councilors being community representatives had the duty to give feedbacks to them. According to Tanzania administrative setup, each ward should have a councilor who is normally elected by village members (aged >18 years). A Ward may consist of more than three villages.
\nLocal communities were further probed to comment on whether the ban has led to conflicts or not. Results indicate that in Natta Mbiso and Machochwe, 92% had the view that the decision has not led to conflicts (Figure 3). However, in Park Nyigoti, 62% argued that the ban has led to increased conflicts. Human-wildlife conflicts in particular between elephants and local communities are widespread in Africa and are a major concern for both elephant conservation and rural development [7]. The increase in conflict in this village could be due to its location. The village is almost an island as it is surrounded by several protected areas (Serengeti National Park, IKONA WMA, and Ikorongo Game Reserve). This has made the village to have very little livelihood options mainly because of very limited land for crop production, increased crop destruction, and livestock predation by wild animals.
\nBan and increased conflicts.
Failure to attach conflicts to the ban in Natta Mbiso could be attributed by the socioeconomic benefits local communities are currently enjoying from SGRL. Natta Mbiso currently has a suburban environment as a result of several business enterprises (lodges, hotels, shops, tourist souvenirs, etc.) and the fact that most SGRL employees are settled here. Furthermore, SGRL is currently supporting income-generating enterprises to adjacent communities. As for Machochwe, the possible explanation could be continued poaching as the village boundary is very close to SNP and therefore easy to poach without being easily noticed. In some parts park boundaries are less than a kilometer from the village boundary (Senior Author, pers. Obs.).
\nCommunities had the view that probably the hunting ban has led to increased social services infrastructures (e.g., construction of water wells and dispensary) particularly in Park Nyigoti and Machochwe villages (Table 2). The question of what happens to local people is one that remains poorly addressed in conservation literature. This is because it is being produced in an institutional and ideological climate in which there is a widening gap between rhetoric and reality [8]. In such a context [9], it becomes easy to present facile paradigms of how local people will participate in and benefit from conservation interventions.
\nPark Nyigoti | \nNatta Mbiso | \nMachochwe | \n
---|---|---|
Construction of dispensary | \nEmployment | \nConstruction of dispensary | \n
Student scholarships | \nSell of farm products | \n\n |
Increased tourists | \n\n | \n |
Reduced burden on levy | \n\n | \n |
Construction of deep wells | \n\n | \n |
Perceived benefits of hunting ban.
According to the contract between Serengeti District Council and SGRL, the former is obliged to support social infrastructure developments in the district. SGRL apart from the contribution as per contract also have corporate social responsibility of supporting local communities. In Park Nyigoti other perceived benefits include student bursary, increased tourists, and reduced levy contributions. SGRL continues to sponsor District Council staff and local communities to pursue different short and long courses within and outside the country. Employment and increased number of tourists were also mentioned as benefits. Selling of farm products such as horticultural crops, meat, eggs, milk, etc. to SGRL staff was also seen as benefit. As for levies, the contribution of SGRL in supporting socioeconomic projects has to a greater extent reduced local community contributions toward development projects. On the other hand, wildlife experts viewed increased revenue to Serengeti District Council (SDC) as a benefit since before the initiative the Council used to receive an average of US $7000/annum (District Game Officer, Pers. Comm).
\nLocal community’s perceived costs after hunting ban include decreased cash income, food insecurity, malnutrition, increased human-wildlife conflicts, disease transmission, funds’ failure to trickle down to primary beneficiaries, and denial of human rights (Table 3). Resident hunting has denied village governments and/or local communities to sell game meat, and this has directly denied them from realizing cash income. Local communities used to sell excess bush meat and the former Serengeti Regional Conservation Project (SRCP) had community cropping scheme which made communities to access bush meat at a relatively cheaper price than cattle meat. [10] argue that illegal hunting in the Serengeti has been flourishing, despite stringent law enforcement, because its returns were 45 times greater than those provided legally through the Serengeti Regional Conservation Project community cropping scheme.
\nPark Nyigoti | \nNatta Mbiso | \nMachochwe | \n
---|---|---|
Decreased income | \nDecreased income | \nDecrease in income | \n
Increased destructive animals | \nIncreased destructive animals | \nIncreased destructive animals | \n
Protein deficiency/malnutrition | \nLack of game meat | \nFunds do not reach communities | \n
Increased zoonotic diseases | \nIncreased loss of life | \nIncreased loss of life | \n
\n | Increased poverty | \nFood insecurity | \n
\n | Food insecurity | \nDenial of human rights | \n
Perceived costs of hunting ban.
Failure to access bush meat has also led to increased protein deficiency in the area. Bush meat was a relatively cheap source of protein, and now most local communities are unable to buy cattle meat due to high price attached to it. During the time of survey, the price of a kg of meat stood at TZS 4000 (US $ 3). This is a relatively high price taking into account the fact that the majority live below a dollar per day. According to [11], per capita income of communities adjacent to Western Serengeti National Park was about US $ 280/annum, an equivalent of US $ 0.77/day.
\nIncreased human-wildlife conflicts were also seen as costs inflicted to communities. The conflicts are of different forms ranging from loss of life due to increased wildlife particularly elephants, transmission of zoonotic diseases to domesticated cattle, and crop destruction by wildlife. Other costs were denial of human rights to access wildlife use contrary to the country’s wildlife policy and failure of funds to reach the wider community. The Tanzania Wildlife Policy has the following statement related to wildlife use: “Resident hunting is the right of indigenous Tanzanians to have legal access to wildlife use” [4]. During informal discussion with one resident in Natta Mbiso (located close to SGRL) who preferred anonymity had this to say: “SGRL objective is not for conservation and development but to protect her lodges from disturbances (increase visitor attraction) as they own several lodges in the area including her luxurious lodges such as Sasakwa lodge, Sibora-Grumeti lodge, Zebra-Grumeti, Serengeti, Banguesi, Ramahi and Farufaru lodges.”
\nBetween 2004 and 2011, the Serengeti District Council received compensation from SGRL amounting to TZS 863 million (US $ 375,217) which in essence was supposed to be used for initiating or improving socioeconomic projects (Table 4). Taking into account the fact that the district has more than 50 villages, one can argue that the amount disbursed per village is too little to make an impact on people’s livelihood. For example, if the compensation is equally distributed among 50 villages forming the district, each village will get approximately TZS 4 million/annum (US $ 1739) or TZS 11,000/day (US $ 4.8). With the current average household size of six people in the district, each household is likely to receive about TZS 1833/day (US $ 0.8). By all standards this is very little money for any meaningful poverty reduction contribution at community level. The game species commonly hunted by residents are mainly impala, Thomson’s gazelle, wildebeest, topi, eland, buffalo, bohor reedbuck, and Grant’s gazelle. Other wildlife species counted during the survey were the elephant, giraffe, hartebeest, and zebra.
\nYear | \nAmount in USD (US $*) | \n
---|---|
2004 | \n18,000 | \n
2005 | \n75,000 | \n
2006 | \n85,000 | \n
2007 | \n85,000 | \n
2008 | \n71,430 | \n
2009 | \n142,850 | \n
2010 | \n137,900 | \n
2011 | \n133,300 | \n
Total | \n727,000 | \n
SGRL revenue contributions 2004–2011.
1 USD = TZS 2300; NA = not applicable.
Source: DGO Office—Serengeti District Council.
The population trends for selected wildlife species in IKONA WMA, that is, impala, Thomson’s gazelle, wildebeest, buffalo, and eland, are presented in Figures 4–8. These species are preferred for bush meat.
\nPopulation trend of impala.
Population trend of Thomson’s gazelle. Source: Goodman [6].
Population trend of wildebeest.
Population trend of buffalo.
Population trends for species not in hunting quota. Source: Goodman [6].
Results indicate that for the first 2–5 years after the ban, the population showed an increasing trend before declining for impala, Thomson’s gazelle, wildebeest, buffalo, and eland (Figures 4–7). The increase for the first 5 years before recording a decline could be attributed to fewer disturbances and/or the presence of conducive environment to wildlife. Hunting activities normally disrupt wildlife ecological systems and make wildlife timid and less productive. The reasons for the decline after the fifth year could not be established. However, this can be attributed to poaching as illustrated in Table 5. According to [12, 13], incidences of wildlife crimes and/or animal killed led the wildlife to flee to nearby protected areas and/or distant protected areas particularly for wide-ranging animals such as elephants. The discussion with one elder who preferred anonymity had this to say: “after the ban communities have now intensified poaching to compensate for the previous opportunity of getting bush meat at a cheaper price.”
\nYear | \nWildlife crime incidents | \nAnimals killed | \nTraditional weapon | \n
---|---|---|---|
2003 | \n147 | \n238 | \n1573 | \n
2004 | \n330 | \n824 | \n4826 | \n
2005 | \n342 | \n325 | \n3295 | \n
2006 | \n481 | \n1387 | \n6160 | \n
2007 | \n353 | \n524 | \n371 | \n
2008 | \n300 | \n395 | \n2019 | \n
2009 | \n315 | \n278 | \n1571 | \n
2010 | \n271 | \n406 | \n2792 | \n
2011 | \n361 | \n216 | \n2346 | \n
2012 | \n238 | \n213 | \n848 | \n
2013 | \n266 | \n152 | \n1884 | \n
Trend of wildlife crime incidents, animals killed, and traditional weapons caught.
Source: Mwakalobo et al. [12].
Population trends for other wildlife species (normally not included in hunting quota in the area), namely, elephant, giraffe, zebra, and hartebeest, are presented in Figure 8. Field findings indicate that the population for zebra fluctuated over time, but for the rest (elephant, giraffe, and hartebeest), the population remained constant. For the first 2 years, the population of zebra increased before dropping for 2 years and then rose to the maximum (about 5000) in 2008. It then dropped and rises again. The rise in the first 2 years can be attributed to the safe environment after the ban and availability of habitat. The decline could be associated with hunting for commercial and subsistence. In the study area, zebra meat is highly preferred bush meat by the community due to its deliciousness (Magoiga, pers. comm.).
\nThe study concludes that the ban has significantly boosted the District Council revenues. Despite this positive development, the livelihood of the communities has been significantly affected in many ways including increased human-wildlife conflicts, food insecurity, malnutrition, and lack of bush meat which to many is regarded as cheap source of protein. In addition, the ban led to the increase of wildlife populations particularly in the first 2–5 years. This increase corresponded with increased human-wildlife conflicts as a result of crop destruction and livestock predation. The study recommends the need for involvement of communities in major decisions affecting people’s livelihood such as hunting ban. We also recommend that before instituting hunting ban(s), this has to be informed by research.
\nWe are thankful to the Department of Geography and Environmental Studies, University of Dodoma, for the permission to collect data for this study.
\nAuthors declare no conflict of interest.
Retinoblastoma (Rb) is the most common intraocular malignancy of childhood, but a relatively rare disease, occurring in approximately 1: 16,000–18,000 live births [1]. Its incidence is uniform across populations, with no known gender, racial or ethnic predilection. Rb develops in early childhood, with the vast majority of cases that present before the age of 5 years. The disease can involve one or both eyes and can be inherited from an affected parent or developed de novo in a child with no family history of Rb. This chapter discusses the epidemiological aspects of Rb, including basic concepts in Rb development, incidence and prevalence, age, sex and racial considerations, associated environmental factors, trilateral Rb and secondary non-Rb malignancies.
\nRb can be inherited by an affected parent or developed de novo in a child with no known family history of Rb (i.e., sporadic). The neoplasm can involve one or both eyes and may present in an asymmetrical manner, with different grades in each eye at presentation or even initially appearing as unilateral and becoming bilateral in the course of the disease. The disorder, which is believed to originate from an immature cone photoreceptor cell early in childhood, is initiated in most cases by a mutation in the RB1 gene. RB1 loss initially produces a retinoma, the benign precursor of Rb, and causes genomic instability that subsequently leads to the cancerous tumor, Rb.
\nIn hereditary Rb cases, a single RB1 allele is mutated in most or every cell of a child’s body. An additional “hit” in the second allele in the retina will result in clinical Rb. These cases usually present with bilateral and multifocal disease at a median age of 15 months, but can present also in unilateral disease, albeit less frequently. Between 30 and 37% of Rb cases are bilateral [2], and all bilateral cases are hereditary. However, it is estimated that up to 18% of unilateral cases are also hereditary [3]. This emphasizes the importance of genetic testing in addition to clinical examination, as it has direct impact on the recommended screening frequency of the fellow eye and occasionally on management decisions.
\nNon-hereditary cases (i.e., somatic) usually present at a later age (median: 24 months) with unilateral unifocal disease. In order for the disease to develop in this scenario, two consecutive “hits” occur in a retinal cell, resulting in both RB1 alleles mutated and the development of clinical Rb.
\nAll familial cases are hereditary, but not necessarily vice versa. A mutation can occur at or after conception in an individual with no family history of Rb, and depending on the stage at which it occurs, some of the fetus’ cells will have a mutated RB1 allele, resulting in mosaicism. Children with mosaicism are at increased risk of developing Rb. The disease in this scenario is not inherited, hence siblings of the proband are not at risk, but offspring potentially are, and therefore should be screened soon after birth.
\nHereditary Rb has been associated with an increased risk of developing secondary non-Rb malignancies [4, 5], including sarcomas, carcinomas, malignant melanoma, and neuroectodermal cancers. Secondary tumors were reported to occur in up to 20% of cases in 10 years and the incidence was reported to directly correlate with the time lag from initial diagnosis. It is also well established that treatment by radiotherapy increases the risk of developing secondary tumors, both in and outside the field of radiation [6]. Draper et al. showed in a series of nearly 400 hereditary cases that close to 10% developed secondary malignancies, mainly osteosarcomas, most of which were in the field of radiation [6].
\nTrilateral Rb is a syndrome consisting of unilateral or bilateral hereditary Rb associated with an intracranial neuroblastic tumor that develops most often in the pineal gland (i.e., Pinealblastoma). On a meta-analysis by Kivelä [7], 2% of trilateral Rb cases had a brain tumor but no intraocular Rb, 12% had unilateral Rb and the remaining had bilateral disease.
\nThe reported incidence of Rb is constant worldwide at one case per 16,000–18,000 live births [8, 9]. In 2009 the estimated global annual incidence of Rb ranged from 7200 to 8100 children. The global birth rate has dropped since then, from 20.3 to 18.6 births per 1000 population, but the world’s population has grown from 6593 to 7550 million [10], resulting in an estimated 7800–8800 newly diagnosed Rb cases globally in 2017. The highest disease prevalence is recorded in areas with high birth rates, which is the case of many low- and middle-income countries (LMICs).
\nOver 80% of the newly diagnosed cases are in LMICs in Asia and Africa (Table 1 and Figure 1) [3]. These regions also show the lowest survival rate, reporting up to 70% mortality from Rb. Only about 15% of children with Rb reside in high-income countries, and their prognosis is considered to be very good, with an estimated disease-free survival rate of nearly 100% [11].
\n\n | High incidence (1:16,000) | \nLow incidence (1:18,000) | \nAverage incidence | \n
---|---|---|---|
n | \nn | \nn (%) | \n|
Continent | \n\n | \n | \n |
North America | \n273 | \n242 | \n258 (3.1) | \n
Latin America and the Caribbean | \n669 | \n595 | \n632 (7.7) | \n
Africa | \n2567 | \n2282 | \n2425 (29.5) | \n
Asia | \n4656 | \n4139 | \n4398 (53.5) | \n
Europe | \n504 | \n448 | \n476 (5.8) | \n
Oceania | \n37 | \n32 | \n35 (0.4) | \n
National income level | \n\n | \n | \n |
Low | \n1413 | \n1256 | \n1335 (16.2) | \n
Lower-middle | \n4221 | \n3752 | \n3987 (48.5) | \n
Upper-middle | \n2272 | \n2020 | \n2146 (26.1) | \n
High | \n800 | \n711 | \n756 (9.2) | \n
Estimated number of newly diagnosed retinoblastoma patients in 2017.
Estimated average number of newly diagnosed Rb patients in 2017 by national income level. Income level data source: United Nations, Department of Economic and Social Affairs PD [10].
According to the World Health Organization’s compendium of data from cancer registries, the average Rb incidence rate in children aged 0–4 years is >10 per million compared to <1 per million in children aged 5–9 years, and significantly lower beyond that age [12].
\nIt is difficult to accurately estimate the time at which Rb tumors first develop as information about the biological development of the disease is essentially lacking. There are three important time points associated with Rb development and the time of Rb diagnosis. These include (1) retinal tumor growth following two RB1 mutative events, (2) parents/guardians noticing the first ocular sign, and (3) presentation to an Rb center, at which diagnosis is made and treatment given.
\nAs discussed earlier, the median age of presentation for bilateral cases is 15 months, while for non-hereditary cases is 24 months. Most of the available knowledge originates from familial cases in high income countries, where Rb centers commonly perform screening tests for patients at risk (i.e., siblings of probands). Screening allows detection of small tumors very early in the course of disease, relatively soon after they develop. However, since sporadic cases are not screened, we rely only on age of presentation at two time points. First, the time at which the parents/guardians notice an ocular abnormality, it is usually a white pupillary reflex (i.e., leukocoria). Second, the time at which the final diagnosis is made, which is dependent on the time it takes the patient to reach the Rb center in the referral pathway.
\nThe body of knowledge on Rb is based on retrospective studies, hence, the most accurate data in this context reports the age of the child’s first presentation at an Rb center. Nevertheless, several studies have investigated the lag time from the first ocular sign as noticed by parents, to the presenting sign at the Rb center. In this respect, a huge gap exists between high-income countries and LMICs. In the UK, the referral time from sign onset to visiting primary care was found to be 28 days, primary care to ophthalmologist 3 days, and the time from local ophthalmologist to an Rb Unit was 6 days. In low-income countries, these time lags are considerably longer, and can take 6 months or more [13].
\nRarely, Rb can develop in adults older than 20 years of age, with fewer than 50 case reports found in the literature. Adult-onset Rb is quite different in its presentation compared to its pediatric form, and due to its rarity, it is usually not considered in the differential diagnosis, often leading to delay in diagnosis.
\nIn trilateral Rb [7], rates of familial Rb, the age at diagnosis and laterality were found to be similar to ordinary hereditary Rb. Cases of suprasellar trilateral Rb, however, were diagnosed at an earlier age as compared to Pinealblastoma. The median age of Rb diagnosis was 5 months, and cases of familial Rb were diagnosed at an earlier age than non-familial cases.
\nThere is no known gender predilection in Rb, and although this notion is widely quoted in many scientific reports in the field, it has not actually been thoroughly investigated. Based on data available from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute, Tamboli et al. calculated the incidence of Rb in the United States from 1974 to 1985 and found no gender differences [14]. Gurney et al. used the same data source for similar years (1974–1989), but concluded that rates of Rb were higher in females [15], and Wong et al., in contrast, found an excess of Rb cases in males using the SEER database for the years 2000–2009 [8]. RB1 gene is located on chromosome 13 and there is no known relation to any of the sex chromosomes. There is also no evidence of an association between sex hormones and Rb. Cases of trilateral Rb do not show any gender predilection either [7].
\nSimilar to sex, there is no known association between race and Rb, although some exceptions have been reported. Gurney et al. found higher rates of Rb in blacks as compared to whites in the United States [15]. Broaddus et al., in contrast, found that the overall mean age-adjusted incidence of Rb was 11.3 for Caucasians and 13.0 for blacks, with no significant difference between the two populations [8]. Krishna et al. examined the incidence of Rb using data from the International Agency for Research on Cancer [16], and found no significant difference between white populations in the United States and Europe/Australia, Hispanic populations in Spain and the United States, and Hispanic populations in Uruguay and the United States. They concluded that Rb incidence is similar among varied populations.
\nSeveral studies have shown a link between human papillomavirus (HPV) and the development of sporadic Rb [17, 18]. Shetty et al. analyzed enucleated eyes with Rb and found that 70% were positive for HPV [17], suggesting that the virus may play a role in the development of sporadic RB. Anand et al. tested the presence of HPV in Rb tissue (formalin-fixed paraffin-embedded tissue and fresh-frozen specimens) and found that nearly a quarter of the specimens were positive for HPV [19]. However, the implications of the presence of HPV in Rb tissue and its role in carcinogenesis warrant further study. Jemal et al. investigated the relation between Rb incidence and ultraviolet (UV-B) radiation levels in the SEER program and found no statistically significant correlations [20]. To the best of our knowledge, there are no other reports focused on any additional environmental factors in association with Rb development.
\nRb is the most common primary intraocular malignancy of childhood. The disease can involve one or both eyes and can be inherited or sporadic. The incidence of Rb is stable worldwide at one case per 16,000–18,000 live births. The average Rb incidence rate in children aged 0–4 years is >10 per million compared to <1 per million in children aged 5–9 years, and significantly lower beyond that age. In 2017, globally, an estimated 7800–8800 Rb cases were newly diagnosed. Over 80% of these are in LMICs in Asia and Africa.
\nSo far, there is no validated evidence that retinoblastoma incidence is associated with gender, ethnicity or geographical factors. Studies have shown the presence of HPV in sporadic Rb tissue. Its role in carcinogenesis and the development of sporadic Rb warrants further investigation.
\nWe lack accurate information about the biological development of Rb which creates difficulties in estimating the time at which Rb tumors first develop. In familial cases from high-income countries, genetic screening is routinely conducted. However, in low-income countries this is not the case, and in all settings sporadic cases are not screened. In these cases, we rely on time of presentation, which is strongly influenced by the referral pathways in different settings.
\nSurvival rates are related to the time taken for the child to present at an Rb center and vary greatly between countries: while almost all Rb cases from high-income countries survive, cases in LMICs have a mortality rate of 70%.
\nNo conflicts of interest to disclose.
IntechOpen is the first native scientific publisher of Open Access books, with more than 116,000 authors worldwide, ranging from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery. Established in Europe with the new headquarters based in London, and with plans for international growth, IntechOpen is the leading publisher of Open Access scientific books. The values of our business are based on the same ones that any scientist applies to their research -- we have created a culture of respect, collegiality and collaboration within an atmosphere that’s relaxed, friendly and progressive.
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