PNB quarterly narrative data report July to Sept 2017
27. 27 capturing should be reviewed taking into consideration of the needs of MDAs and by also intensifying engagemen ts with the MDAs .
6. 6 Figure 9 : Distribution between Districts in Q2 2017 Figure 10 : Distribution between Districts in Q3 2017 Figure 11 below, which displays the distribution of reports by months between Districts , shows a high variance in distribution patterns. Figure 11 : Distribution of reports between Districts in first 12 months In the previous section, it was argued that the volume of reports depended on the level of outreach. Since the outreach by the CSO Animators is a local variable, this can explain the shifts in reporting level s , where for instance Kenema received a significant proportion of reports from December 2016 to March 2017, but hardly receive d any in August/September 2017.
11. 11 and service provider is very limited, which reduces the instances where corrupt practices can occur. The low levels of reporting reduces the data se t, the representational value of the data and increases the volatility. Figure 17 : Electricity reports and Districts in Q3 of 2017 Western Area Urban accounted for 56% of all reports on the Electricity Sector , which is higher than the averages frequency of 44% of all reports concerning Electricity coming from Western Area Urban (table 2). Figure 18 : Electricity and Services in Q3 of 2017
3. 3 using the App requires a smart phone and data, it is not considered to be the most a ccessible means of reporting for the general public. Therefore , we assume d that the majority of PNB Mobile App reports are generated as a result of the CSO animator’s outreach. Figure 2 shows the source of the reports received by the PNB Campaign. Figure 2 : Distribution of reports by Source in first 12 months by month There is a clear correlation between the number of reports received in Figure 1 and the PNB Mobile App reporting in Figure 2 . Hence, if the majority of reports on the PNB Mobile App are d erived from CSO Animator activities, it is reasonable to assume that the volatility of the PNB reporting level is a consequence of the activity level of the CSO Animators. Strategic Re - orientation of Outreach Activities The PNB Campaign identified relian ce on CSO Animators facilitating reports to be an issue for the sustainability of the programme. A new outreach strategy aimed at increasing the number of self - reporting of the citizens were devised in August/September. It is expected that reporting will i ncrease significantly as the new strategy is implemented and outreach activit y levels pick up after the rainy season. As indicated , the volume of report s shown by the PNB Data does not necessarily represent changes in the level of bribery or honest officials, but the intensity of outreach activity. Consequently, the raw numbers of report s are do not necessarily reflect trends in level of bribery. The next section will explore another way to perceive trends: the changes of distribution between indicators.
21. 21 “New Connection” was the most frequently reported service (43%), as it also was the case for the Electricity Sector. The second highest was “Illegal Connection” with 33%, which may suggest challenges for the Water com panies in limiting/controlling these. The dismantling of Illegal Connection is also a human intervention and not an automatic, which makes it more vulnerable for bribery. Figure 30 : Distribution of Water Sector reports between Services in 12 months On an average since inception, Illegal Connection has constituted 17% of the Water Sector reports and it is therefore significantly higher with 33% in the 3 rd quarter of 2017. Otherwise, figure 27 show the high degree of volatility of the data relating to th e Water Sector, which is a consequence of the low level of reporting.
26. 26 Figure 38 : Age distribution per sector in Q3 2017 The youth (15 - 29 years) accounted for the majority of reporting to the Education sector. In the Health sector , it was primarily young and adult women, whereas for the police , it is young and adult men. The above 50 years old had the highest reporting ratio on Electricity, Water and Others. The above demographics of reporting reflects the user demographics in the va rious sectors; Young people attends educational institutions , pregnant women and mot her s t ake children for Health Care, the commercial drivers are primarily men , the people able to have water and electricity installed are of a certain age, before they afford accessing these services . That is the reason why the 15 - 29 years have the majority of reporting for Education, Women for Health Care, Men for Police and few young people reports on Electricity and Water. 6. Actions points for the PNB Programme Hi gh dependence on CSO animators to encourage the public to report is a cause for concern as this has the potential to increase the volatility of reporting thereby making trend analysis less feasible and reduces the sustainability of the programme. As a re sult, i n order to encourage the public to make their reports directly into the PNB Pla tform, the PNB Programme should focus more on the outreach activities that promote self - reporting. This can be accomplished by focusing the communication on the positive achievement of the PNB Programme . That is, the actions taken by the MDAs to reduce bribery and improve service delivery, as well as further sensitizing the public on how to self - report without a CSO animator being present. The above requires that the PNB produces actionable data and provides support to the MDAs in identifying areas of concern and possible actions to address these. Hence, the data
9. 9 average (15%). On the oth er end of the scale, Western Area Urban only received 11% of the Education reports compared to 36% of all reports. Hence, reporting on the Education Sector was relatively higher in Bombali and Kenema compared to the other districts, while it was significan tly lower for Western Area Urban. Figure 14 : Disaggregation of Reports in Services for Education (Q3 2017) In the 3 rd quarter “Grades and Exams” where the most frequently reported services in Education. From the inception of the PNB Campaign in the end of September 2019 , Education has been the most volatile sector in terms of seasonal changes on the m ost and least reported services, as show in figure 15 below. Figure 15 : Distribution of Services reported under Education
25. 25 There is almost an equal gender distribution in the overall PNB reporting. While the overall gender distribution is equal there are variances between the various sectors. Figure 35 : Gender distribution per sector in Q3 2017 Most sectors had a relatively equal gender distribution apart from Health Care, which is primarily women reporting, and Police, where men accounted for the majori ty of reporting. Figure 36 : Age d istribution in Q3 2017 Figure 37 : Average age d istribution 12 months The age distribution of the 3 rd quarter of 2017 was similar to the yearly average with a minor increase in Above 50 Years reporting ratio and a minor decline in 30 - 49 years reporting.
12. 1 2 During the 3 rd quarter “New Connections” was most frequently reported with 39% of all reports, followed by “Meter Replacement” (25%) and “Reconnection” (22%). Figure 18 : Distribution of reporting on Services for Electricity in 12 month In the last year of the programm e there has been minor fluctuations as seen in Figure 18 . H owever, on average , distribution is relatively close to the Q3 data with 40% for “New Connections”, 22 for “Meter Replacement” and 25% for “Reconnection. The reason for the fluctuation is most like ly the volatility caused by a relatively small dataset. It is noticeable, that while “Reduced Bill” initially was scoped as an important issue for bribery in the Electricity sector, there has only been few reports on it. This can be attributed to the imp lementation of pre - paid meters by EDSA, which reduces the opportunities for corrupt practices in the providing electricity. The services with the highest level of reporting are, on the contrary, those with a high degree of human interaction (New Connection , Meter Replacement, and Reconnection ). In February to April, Meter Replacement had an increase in reporting ratio. In this period EDSA was challenged by supplying new meters, which generated delays for the costumers. The discontent and/or attempt to circumvent the delayed process could be the c ause of the upsurge in Meter Replacement reporting during that period.
18. 18 Since the start of the PNB programme, the Health Care Sector has received 39% of all reports in respect of “ I did not pay a Bribe” or “I met an Honest Official” , because it is a sector where users are more inclined to show appreciation. Ho wever, the concentration of reports at few services and locations is an issue which the programme should look into . This could likely be as a result of a high degree of appreciation by the public, sensitization at the specific location carried out by the s taff, false reporting or an error in the data capturing multiplying the number of reports. Figure 27 : Distribution of Health Care Sector reports between Services in 12 months The Health Care Sector has experienced a relatively stable distribution of re ports, with at an average 32% for “Under 5 - child health” and 32% for “Pregnancy and Child Birth”, which is relatively close to the 3 rd quarter distribution. The high level of reports concerning these services can be attributed to the widespread public awareness about these service under the free health care . This has made easier for the public to recognize if illegitimate charges are added (I Paid a Bribe) The high levels of report in this sector can also be attribut ed to the level of appreciation when service is delivered (I met an Honest Official).
16. 16 programme had a high freque ncy for “Traffic”, it could suggest that the interventions of SLP targeting traffic related bribery in Kenema has had a positive effect. Health Care Sector 27% of the reports made by the public in the 3 rd quarter of 2017 related to the Health Care sector, which is exactly the same ratio as for the first 12 months of the PNB Programme. Figure 25 : Disaggregation of Health Care Sector reports in Districts in Q3 2017 The most noticeable on the district disaggregation of Health Care reports is the high number of “I did Not Pay a Bribe” reports from Western Area Urban, combined with the relatively low number of “I Paid a Bribe” reports from the same location and from Bo District.
5. 5 With regards to the distribution of reports between Sectors, a similar picture emerges when comparing the 2 nd and 3 rd quarter of 2017, with an almost identical distribution despite a large variance in the number of repor ts received. Figure 6 : Distribution between Sectors in Q2 2017 Figure 7 : Distribution between Sectors in Q3 2017 Over 12 month period, few variances can be detected but overall the report distribution remains relatively stable month after month (see figure 8). Figure 8 : Distribution of reports between Sectors in first 12 months The distribution of reports in the targeted Districts, however, changed significantly from the 2 nd quarter to the 3 rd quarter of 2017 , as shown in figure 9 and 10. In Kenema District, for instance, reports dropped from 30% of all reports in Q2 to 15% in Q3.
20. 20 The overall distribution can represent the way in which service is delivered in the capital vis - à - vis the Districts, where the former has many large hospitals and the service in the latter is delivered at a multitude of smaller Clinics and PHUs. The highe r frequency of “I Paid a Reports” in the districts, could suggest that the challenges with delivering Health Care services without invoking additional charges are higher in the district than in the capital. The CSO animators reports that there are challeng es with both supplies and payment of staff in the districts, which could be the cause of such issues. Water Sector The Water Sector has an even lower level of reporting than the Electricity Sector with an average of only 2% of the total number of reports (figure 12) and 3% in the 3 rd quarter of 2017. Being a utility sector with a limited penetration, just like the Electricity Sector, similar factors of limited distribution and infrequent interaction with service providers apply. The extremely low l evel of reporting make the date even more vulnerable to representational reporting and subject to a high level of volatility. Figure 28 : Disaggregation of Water Sector reports in Districts in Q3 2017 93% of all reports relating to the Water Sector der ived from Western Area Urban in the 3 rd quarter of 2017. That is a significantly higher than the average of 71%. On the same token, the ratio of reporting from the other districts declined correspondingly. Figure 29 : Disaggregation of Water Sector reports between Services in Q3 2017
14. 14 The district distribution of reports differed significantly from the yearly average in table 2. Western Area Urban had, mainly due to a large number of “I did not pay a Bribe” reports, higher frequen cy than the yearly average (47 % Q3, 35% year), just as Western Area Rural (20% Q3, 10% year) and Bombali ( 19 % Q3, 16% year). On the opposite spectrum, Kenema reduced its frequency from 31% yearly average to 11% in Q3. Bo only received 3% of all Police reports in the 3 rd Quarter. This variance from the genera l trend can either be seen as a result of the SLPs actions in Kenema in response to the PNB Data, or as caused by the decline in reporting from Kenema in the 3 rd quarter of 2017 (figure 9 and 10). Since Kenema during the first 12 months of the programme ha d a relatively high average on Police reporting (table 2), the decline is most significant in this sector. Figure 22 : Police reports by Sectors in Q3 2017 “ Traffic” remain ed the most commonly reported service followed by “Bail” .
22. 22 Figure 31 : Disaggregation I Paid a Bribe reports in Districts and Services in Q3 2017 15 of the 36 I Paid a Bribe reports on “Illegal Connection” in Western Area Urban came from Juba and 32 of 45 reports on “New Connection” from Portee. However, the GUMA Valley Water Company has reported that they have not carried out any New Connections in that area. Therefore , the repor ts could relate to other private service providers, as suggested by the CSO animator in the area . This implies that an indication of the service provider could be a useful addition to the PNB reporting platform. 4. Distribution of Method of Payment and Value of Payment per Sector Paying a bribe cannot be reduce d to the transfer of cash. Bribes can also be in Services and Favour, Products or Sexual Favours. K nowledge on the nature of bribes for specific sectors/services can be valuable in designing targeted sensitization and responses to these sectors/services. Figure 32: Distribution of Method of Payment in Q3 2017 Figure 33 : Average Distribution of Method of Payment
15. 15 Figure 23 : Distribution of reporting on Services for Police in 12 month Since inception this pattern has been consistent with “Traffic” accounting for 69% and “Bail” for 17% of all Police Reports. Figure 24 : I Paid a Bribe reports for Police in Q3 of 2017 W hile “Bail” only constitutes at an average 17% of all re ports relating to the Police, 35 % of all reports in Western Area Urban in the 3 rd quarter of 2017 related to “Bail”. This significant variation from the average mainly derived from two location in the East - End of Freetown: Kissy (74) and Up - Gun (69). Furthermore, it is noticeable that "Traffic” only constitutes 50% of the Kenema reports, which is below the average of 69%. Particularly considering that Kenema earlier in the
13. 13 Figure 20 : I Paid a Bribe reports for Electricity in Q3 of 2017 Report s on the Electricity sector are generally focused on few locations. In the 3 rd quarter of 2017, all 18 reports o n “Reduced Bill” came from Makari Gbanti in Bombali . 32 of 50 reports on “New Connection” in Western Area Urban came from Portee and 13 of 30 reports on Meter Replacement in Western Area Urban came from Juba. These “hotspots” can either be caused by the te ams working in the area, the activity of the CSO animators or misrepresentation caused by a too small dataset. Sierra Leone Police The Police received a total of 2345 reports in the 3 rd quarter of 2017 , which is 40% of all reports captured by PNB in the p eriod and slightly below the yearly average of 42% (figure 7 and 12). Of the reports 1719 related to “I Paid a Bribe, 504 to “I Did Not Pay a Bribe” and 122 on “I Met an Honest Official”. Figure 21 : Distribution of Police reports in Districts in Q3 2017
2. 2 1. Overall number of reports received During the third quarter of 2017 , the PNB Campaign received 5 , 768 reports . This represents a significant de crease of 4 9.5 % in comparison to the 11 , 424 reports received in the previous quarter . The reporting levels to the PNB Campaign has been volatile throughout the campaign as illustrated in Figure 1. The ste e p decline in the 3 rd quarter of 2017 shows clearly on the chart, with a decline from a total of 4329 reports in June 2017 to just 660 inc oming reports in September 2017. Despite the volatility there has been a sli ght upward trend in reporting since inception on the 26 th of September 2017. Figure 1 : Distribution of reports in the first 12 months . The figure above show s 3 major declines in reporting levels in January, May and August/September 2017. Common for the 3 periods were a decline in outreach activities, particularly the animation activities, carried out by the partnering CSOs. In January 2017, there w as a delay in CSO Animators resuming work after the holiday season and the PNB Campaign received very few reports in particularly the first 2 weeks of January. In May 2017 Coffey, the implementing partner of the PNB Campaign, had administrative challenges with regar ds to the agreement with the CSOs, which lead to a reduced animation and outreach by the CSOs. I n August/September the PNB developed a new strategy for PNB outreach and sensitization which led to reduced activity levels during the period , as well as the w et season which reduced intensity of the CSO Animators outgoing activities. There is reason to believe in a strong correlation between CSO Animators activity and the level of reporting. All CSO animators carry a phone with the PNB Mobile Apps installed. T he CSOs indicate that they primarily used the PNB Mobile Apps to facilitate reports, whenever someone wished to submit a report but did not have the means to do so. Since,
4. 4 2. Distribution of report – a new way to perceive trends Despite the drop in the overall number of reports between the 2 nd and 3 rd quarter s of 2017 , they remai n more or less equally distributed between “I Paid a Bribe”, “I Did not Pay a Bribe” and “I Met an Honest Official”. Figure 3 : Distribution of reports in 2 nd quarter 2017 Figure 4 : Distribution of reports in 3 rd quarter 2017 Seen across all 12 months of the programme on figure 5 , it is clear that the distribution of reports among “I Paid a Bribe”, “I Did not Pay a Bribe” and “I met an Honest Official” is relatively stable , with an average of 76% “I Paid a Bribe”, 17% “I Did not Pay a Bribe” and 8% “I met an Honest Official” Figure 5 : Distribution of reports by What Happened in first 12 months Hence, despite the volatility of reporting level (as shown in figure 1), the distribution of reporting between the indicators are m ore or less constant (figure 5).
10. 10 Figure 15 shows that in April to July there w as a high frequency of reporting on “Grades and Exams”. In July and August, “Report Card” w ere frequently reported, while in August and more so in September, “Admissions” w ere the most reported service. This reporting pattern refl ect s , with a slight delay , the school calendar year. Hence, the PNB reports about services provided by the Education sector reflect the school calendar. Since the provision of services within the Education sector is seasonal, it is not suitable to benchma rk one month to the next. However, information of the seasonal occurrence of bribery for certain services can be used to do time specific sensitization and interventions. Figure 16 : I Paid a Bribe for Services each District (Q3) “I Paid a Bribe” reporti ng on “Grades and Exams”, which were the most reported, had high frequency in all Districts apart from Western Area Urban. Reporting on “Report Cards” followed a similar pattern as “Grades and Exams”, since they are related services as the Exams leads to t he issuing of Report Cards. Notably, reporting on “Others” almost solely derived from Bombali and Kenema Districts. Based on the feedback provided by the Call Centre operators, who receive reports directly from the public, we know that a large proportion of reports on “Other s ” in the Education Sector relates to the School Feeding Programme. The high level of reporting from Bombali Di strict, and particularly Bombali Shebora, is a concern, since it is significantly higher than the cross sector average. Fur thermore, the reporting on “Others” could indicate challenges for the School Feeding Programme in Bombali and Kenema District. Electricity Sector Electricity only receives on an average 4% of the reports, which is exactly the same ratio as in the 3 rd quarter (figure 7 and 12). The relative low level of reporting is likely due to two factors: distribution of service and level of interaction with service providers. Electricity services are not accessible in most parts of the country, which reduces the n umber of potential users significantly. Secondly, after initial installation the interaction between user
17. 17 Figure 26 : Disaggregation of Health Care Sector reports in Services in Q3 2017 “Pregnancy and Child Birth” accounted for 33% and “Under 5 Child Health” for 27% of the reports to the Health Care Sector in Q3. A significant proportion of these were “I did not pay a Bribe” particul arly from Western Area Urban. Figure 27: “Pregnancy and Child Birth” and “Under 5 Child Health” in Western Area Urban Q3 The “I did not Pay a Bribe” reports constituted 92% of all reports relating to “Pregnancy and Child Birth” and “Under 5 Child Health” in Western Area Urban. In Western Area Urban 73% of these reports came from Ola During Ch ildren ’ s Hospital and 26% from P C M Hospital . 4028 50 66 38 25 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Cash Other Products, Animals or Food Service and Favours Sexual Favours Total Total
1. 1 Quarterly Data Analysis for PNB Reporting Platform 26 th June - 26 th September 2017 This re port presents data for the 5 sectors of the PNB Campaign (Education, Electricity, Health Care, Sierra Leone Police , and Water) from the Pay No Bribe Reporting Platform for the period, 26 th June – 26 th September 2017 . The data represent reports received from the public under the three reporting mechanisms: The 515 hotline; Mobile Apps ; and Website. The data present repo rting from the 5 implementing districts of Bo, Bombal i , Kenema, Western Area Urban and Western Area Rural. D ata is presented under the following headings: 1. Overall number of reports received ................................ ................................ ................... 2 2. Distribution of report – a new way to perceive trends ................................ ....................... 4 3. Distribution of reports received under each sector ................................ ............................ 8 Education ................................ ................................ ................................ ........................... 8 Electricity Sector ................................ ................................ ................................ .............. 10 Sierra Leone Police ................................ ................................ ................................ .......... 13 Health Care Sector ................................ ................................ ................................ ........... 16 Water Sector ................................ ................................ ................................ ..................... 20 4. Distribution of Method of Payment and Value of Payment per Sector ........................... 22 5. Demographics of reporting ................................ ................................ .............................. 24 6. Actions points for the PNB Programme ................................ ................................ .......... 26
7. 7 W hil st the volume of reporting fluctuates due to th e level of outreach activities, the distribution of reports between “I paid a Bribe”, “I did not Pay a Bribe”, “I met an Honest Official” between the Sectors are more or less constant. This “standard distribution” can therefore serve as a baseline for the data, and help determine whether a sector nationally or in a specific location is performing better or worse over time. However, “standard distribution” cannot be used to compare the overall performance of locations, since the volume of reporting in the location are determined by the level of outreach. Figure 12 : Baseline d istribution of reports between sectors in first 12 months Note that local variances are not caused by the level of outreach, but also of differences in sectors and services delivered in particular areas Table 1 : District baseline d istribution of reports between sectors in first 12 months Education Electricity Health Care Police Water Other Bo District 21% 5% 29% 41% 1% 3% Bombali District 31% 5% 30% 29% 0% 5% Kenema District 20% 2% 29% 40% 1% 7% Western Area Rural 20% 2% 28% 49% 1% 0% Western Area Urban 10% 7% 21% 53% 4% 4% Grand Total 20% 4% 27% 42% 2% 5% Table 1 shows that there are recognizable differences in the distribution of reports in the Districts. For Education, Bombali District received 31% while Western Area Urban received only 10%. For Electricity and Water, the highest frequency was in Western Area Urban (7% and 4%), which is surprising since these are services mainly provided in urban areas. Health Care was relatively equally distributed, whereas for the P olice s ector Bo mbali stands out with only 29% of the reporting.
8. 8 Table 2 : Sector baseline d istribution of reports between districts in first 12 months Education Electricity Health Care Police Water Other Total Bo District 9% 11% 9% 9% 4% 5% 9% Bombali District 35% 24% 25% 16% 3% 24% 23% Kenema District 34% 17% 35% 31% 17% 47% 33% Western Area Rural 8% 4% 9% 10% 5% 1% 8% Western Area Urban 13% 44% 22% 35% 71% 24% 28% T he following sections explore the data of the 3 rd quarter of 2017 at both district and service level s . 3. Distribution of reports received under each sector In this section the distribution of “I Paid a Bribe”, “I did not pay a Bribe” and “I Met an Honest Official” will be presented for each of the 5 sectors of the Pay No Bribe Campaign. Education Education received a total of 1230 reports in the 3 rd quarter of 2017, out of which 1045 were “I Paid a Bribe”, 76 “I did Not Pay a Bribe” and 109 “I met an Honest Official”. While the volume of report on Education decreased si gnificantly from the 2 nd quarter, Education still received 21% of all reports (figure 7), which is very close to the baseline of 20% (figure 12). Figure 13 : Education reports and Districts in Q3 of 2017 Bombali District received 42% of the reports on Education in the 3 rd quarter, which is higher than the cross sector average of 29% for reporting on Bombali District (figure 1). Similarly , Kenema District had a higher ratio of Education reports (16%) compared to the cross sector
24. 24 251.000 - 500.000 SLL 13 8 6 11 8 48 94 Above 500.000 SLL 1 1 3 5 10 Other/Beyond Value 1 1 9 11 Sexual Favours 22 1 1 1 25 Total number of reports 1045 208 900 1719 110 225 4207 Total Mean Value in SLL of reported bribes 31.919. 500 22.233.0 00 27.781. 500 61.106. 500 12.560.5 00 34.341.5 00 189.942.50 0 Average Median Value per Bribery in SLL 31.232 106.889 30.937 35.568 114.186 159.728 45.539 The Police accounted for the highest tota l value of reported bribes paid in the 3 rd quarter of 2017 with a total of 61.106.500 LE . The Police also had the highest number of received reports. “Other Sectors” followed with a total value of 34.341.500 LE , despite having received relatively few reports . The average value for the reported bribes under “Other Sectors” was much higher than the remaining sectors, so even with few report the total value exceeded that of the r emaining sectors. In general, t he average value of reported bribes is lowest in the most frequently reported sectors (Police, Education and Health Care), while being highest in the less frequently reported sectors (Electricity, Water, Other). As describe d previously, Water and Electricity are sectors where there is less direct interaction between the public and the service provider. However, when the interaction is required, for instance to carry out installations, the value of a potential bribe is high. The opposite applies to the Police, Education and Health Care, where the service delivery always involved human interaction. This makes it more vulnerable to bribery , but the value of a potential bribe is relatively low. 5. Demographics of reporting Figu re 34 : Distribution of Gender in Q3 2017 Figure 35 : Average Distribution of Gender 12 months
23. 23 In the 3 rd quarter , Cash had a high prevalence as the most reported method of payment ; 96 % of all “I Paid a Bribe” repo rts . Products , Food and Animals constituted 1,6 % and the rest less than a percentage (figure 32), which is very close to the average distribution of the first 12 months of the programme (figure 33). The extraordinar il y high prevalence of cash as the reported method of payment, can have 2 main causes: 1. The cash is the simplest, easiest and most anonymous way to transfer value, and therefore a preferred method of payments of bribes, 2. That there is an underreporting of bribes paid using other methods of pa yment, since the payee may not recognize services or a favour as bribes, but con siders it similar to a legitimate social gesture. If the former is the case, capturing method of payment is less relevant, since proportion of bribes paid using other methods of payment are not statically significant. I t is a latter , the public should be further sensitized on what can constitute a bribe, so the public knows that providing unwarranted services and favours also can constitute bribery. Table 4 : Method of Payment in Piloted Sectors Cash Products, Animals or Food Service and Favours Sexual Favours Other Grand Total Education 963 32 12 22 16 1045 Electricity 205 3 208 Health Care 837 32 22 1 8 900 Police 1709 1 3 1 5 1719 Water 103 7 110 Other 211 1 1 1 11 225 Grand Total 4028 66 38 25 50 4207 Education and Health Care had the highest frequency of non - cash reported bribes, with Bombali District accounting for 68% of all non - cash reports in Q3 and Western Area Urban only 4%. Education had the vast majority of reports on Sexual Favours (88%) and 18 of the 22 reports came from a single chiefdom in Bombali District. Table 5: Value of Payment in Q3 Education Electricity Health Care Police Water Other Total 0 - 5000 SLL 282 2 134 237 4 2 661 6000 - 10.000 SLL 286 10 236 318 9 3 862 11.000 - 50.000 SLL 295 50 414 818 21 57 1655 51.000 - 100.000 SLL 109 66 86 307 31 55 654 101.000 - 250.000 SLL 36 72 21 24 37 45 235
19. 19 Table 3 : I Paid a Bribe reports for the Health Care Sector in Q3 of 2017 Certificate (health, birth, death) Drugs and Treatment Emergency Care Medical Tests Pregnancy and Child Birth Registration and Consultation Under 5 Child Health Vaccinations Other Grand Total Bo District 3 9 8 13 2 16 1 52 Bo Government Hospital 3 5 8 Government Clinic or PHU 9 3 13 2 16 43 Private or NGO Hospital 1 1 Bombali District 15 35 3 16 102 33 81 2 14 301 Government Clinic or PHU 15 34 1 12 73 28 67 1 13 244 Makeni Government Hospital 1 2 4 29 5 9 1 1 52 Private or NGO Hospital 5 5 Kenema District 8 3 7 8 84 21 82 3 10 226 Government Clinic or PHU 7 3 5 74 1 73 2 10 175 Kenema Government Hospital 1 2 8 10 20 9 1 51 Western Area Rural 39 10 12 41 40 16 56 14 228 Government Clinic or PHU 39 10 12 40 40 15 56 14 226 Private or NGO Hospital 1 1 2 Western Area Urban 5 36 9 30 11 2 93 Connaught Hospital 1 1 Kingtom Police Hospital (MI Room) 1 1 Lumley Government Hospital 3 3 3 9 Macauley Satellite Hospital 1 1 Ola During Children's Hospital 1 16 8 8 1 34 PCM Hospital 7 3 2 12 Prison Hospital 1 1 Private or NGO Hospital 7 1 3 11 Rokupa Government Hospital 1 2 1 4 Wilberforce Military Hospital 1 1 Government Clinic or PHU 1 2 3 10 1 1 18 Grand Total 62 56 31 109 248 102 246 22 24 900 While the “I did not pay a bribe” report s concentrated on few locations in Western Area Urban, the “I Paid a Bribe” report s focused on the “Government Clinics and PHUs” in the Districts. The relatively few reports on “I Paid a Bribe” from Western Area Urban mainly came from Ol a During Children’s Hospital.
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