Models were implemented from 1988 to 1997, first to attain a steady state then reported levels of previous interventions incorporated from 1998 to 2017. As shown in Figs. 2a, 2b, and 2c below, the data were fitted from 2008 to 2017 and predictions made from 2018 to 2030, S1 Figs. 4, 5 and 6.
The most populous of the zones is the Transitional forest with a population of 17.1 million, followed by the Coastal savannah 8.1 million while the Guinea savannah accounts for 5.1 million people (using 2017 zonal estimated population from DHIMS2).
Figure 2: Model run time is 1988 to 2030.Steady state period spans from 1988 to 1997, 1998 to 2017 previous interventions implemented and reporting rates on DHIMS introduced. Data fitting from 2008 to 2017 for the (a) Guinea savannah, (b) Transitional forest and (c) Coastal savannah.
Biting intensity seems to be higher in the Guinea savannah compared to the other zones. As captured in S1 Fig. 7, biting rates in the Guinea savannah could be as high as 170(b/p/m) compared to those of the Transitional forest 12(b/p/m) and 10(b/p/m) in the
Coastal savannah during the peak transmission seasons respectively. S1 Fig. 7 suggests that, even though biting (as well as transmission) seems to occur all year around, in all zones, they peak following rising rainfall.
Estimated burden of all clinical cases of malaria (uncomplicated and severe malaria) in the baseline year of 2018 in the Guinea savannah was 219 (95% p.CI [153, 315])/1000 population and 261 (95% p.CI [220, 312])/1000 population, 139 (95% p.CI [117, 154])/1000 population for the Transitional forest and Coastal savannah zones. However, reported cases of uncomplicated and severe malaria in 2018 at the health facilities were however estimated to be 173 (95% p.CI [121, 250])/1000, 199 (95% p.CI [168, 238])/1000 and 104 (95% p.CI [88, 115])/1000 population in the Guinea savannah, Transitional forest and Coastal savannah respectively.
Results of scaled up interventions implemented for 3 years to achieve universal coverage levels with respect to LLINs and 5 years to achieve targeted coverage levels of IRS in the various zones were simulated from 2018 to 2030 under various intervention scenarios as presented in the following sections below.
Impact of LLIN interventions
LLIN coverage of 70% and 90% at baseline usage (56%, 45% and 35% for Guinea savannah, Transitional forest and Coastal savannah)
The impact of increased universal coverage levels of ITNs/LLINs were tested for the various zones and model simulation results shows that, achieving elevated levels of LLIN coverage of 70.0% and 90.0% at baseline level of protective efficacy of LLINs (40.0%) and IRS (30.0%) while keeping the coverage levels of IRS at baseline (0.0%) at 2018, leads to a 2.5% % and 8.9% reduction in uncomplicated cases in the Guinea savannah, 8.2% and 17.3% in the Transitional forest and 9.9% and 19.8 in the Coastal savannah respectively, Fig. 3a,3b and 3c (S4 Figs. 1a ). Corresponding reductions in reported cases of severe malaria and malaria in pregnancy were observed as in S4 Fig and 1b (S2 & S3 Figs. 1a, 1b and 1c) [20].
For predictions of all reported clinical incidence of malaria (uncomplicated and severe), the corresponding reductions in the in the incidence rates were 169 (p.CI [117, 245])/1000 and 160 (p.CI [108, 245])/1000 population in the Guinea savannah in 2020 and 168 (p.CI [116, 245])/1000 and 155 (p.CI [100, 230])/1000 population by 2030, S5 Table 1.
In the Transitional forest, the incidence rates are 189 (95% p.CI [157, 226])/1000 and 179 (95% p.CI [148, 226])/1000 population in 2020 and 177 (95% p.CI [139, 215])/1000 and 159 (95% p.CI [109, 190])/1000 population by 2030, S5 Table 2.
Incidence rates of 189 (95% p.CI [157, 226])/1000 and 189 (95% p.CI [157, 226])/1000 population for reported cases of all malaria were observed in 2020 whiles 189 (95% p.CI [157, 226])/1000 and 189 (95% p.CI [157, 226])/1000 population were predicted by 2030 in the Coastal savannah, S5 Table 3.
LLIN coverage of 70% and 90% at baseline usage of 60% across zones
When coverage levels are maintained at 70.0%and 90.0%, in all the zones, reductions in predicted uncomplicated cases by 4.2% and 11.3%, respectively in the Guinea savannah, 20.0% and 32.8% in the Transitional forest and 36.9% and 51.3%, in the Coastal savannah are observed by increasing the level of usage of LLINs to 60.0%, S4 Figs. 1a, 1b and 1c and Fig. 4a, 4b and 4c below.
Corresponding cases of severe malaria and malaria in pregnancy observed are shown on S2 & S3 Figs. 2a, 2b and 2c and S4 Figs. 1b and 1c respectively.
The corresponding incidence rates with an increased LLIN usage to 60% in the Guinea savannah are 166 (95% p.CI [114, 242])/1000 and 156 (95% p.CI [104, 230])/1000 in 2020 and 165 (95% p.CI [112, 241])/1000 and 151 (95% p.CI [94, 225])/1000 population by 2030 respectively for LLIN coverage of 70% and 90%, S5 Table 1.
Rates predicted in the Transitional forest for elevated use of LLIN to 60% respectively for LLIN coverage levels of 70% and 90% were 171 (95% p.CI [139, 206])/1000 and 158 (95% p.CI [126, 191])/1000 at 2020 and 148 (95% p.CI [103, 186])/1000 and 113 (95% p.CI [64, 151])/1000 population by 2030, S5 Table 2.
With respect to an increased level of LLIN usage and coverage levels of 70% and 90% respectively in the Coastal savannah, the predicted rates were 77 (95% p.CI [60, 91])/1000 and 69 (95% p.CI [53, 83])/1000 for 2020 and 51 (95% p.CI [26, 78])/1000 and 31 (95% p.CI [12, 58])/1000 by 2030, S5 Table 3.
LLIN coverage of 70% and 90% at baseline usage 80 across zones
A further proportion of predicted cases of reported uncomplicated malaria are averted when the LLINs usage is increased to 80% as shown in and Fig. 5a, 5b and 5c. The proportion of predicted cases averted in the Guinea savannah, Transitional forest and Coastal savannah are 13.5% and 24.4%, 36.6% and 53.2%, and 55.7% and 69.0%, respectively for LLIN coverage of 70%and 90% across all the zones S4 Figs. 1a, and similarly for predicted cases of severe malaria and malaria in pregnancy as shown in S4 Fig. 1b and 1c and S2 & S3 Figs. 3a, 3b, 3c respectively.
At an 80% proper usage of LLINs in the Guinea savannah could lead to a reduction in the rates of clinical malaria reported to 150 (95% p.CI [97, 223])/1000 and 136 (95% p.CI [84, 206])/1000 population by 2020 and 148 (95% p.CI [91, 222])/1000 and 125 (95% p.CI [62, 196])/1000 population by 2030, S5 Table 1.
Similarly for the Transitional forest, the rates of clinical incidence in all cases of malaria could be reduced to 146 (95% p.CI [115, 179])/1000 and 130 (95% p.CI [100, 160])/1000 population in 2020 and 107 (95% p.CI [57, 145])/1000 and 60 (95% p.CI [22, 93])/1000 population by 2030, S5 Table 2.
When LLIN usage of 80% and LLIN coverages of 70% and 90% are implemented successfully in the Coastal savannah, the incidence rates of reported cases of malaria could possibly be reduced to 62 (95% p.CI [47, 77])/1000 and 53 (95% p.CI [39, 67])/1000 population respectively by 2020 and 27 (95% p.CI [10, 55])/1000 and 11 (95% p.CI [4, 28])/1000 population by 2030, S5 Table 3.
Impact of IRS interventions
IRS coverage of 80% and PE of 30% and 60%, LLIN coverage and usage at baseline levels (66% and 56% in the Guinea savannah, 51% and 45% in the Transitional forest and 50% and 35% in the Coastal savannah respectively)
On average, annual predicted cases of uncomplicated malaria averted close to 90.0% at various levels of PE, if an 80% IRS coverage target were attained in five years and maintained through to 2030 across zones as showed in Fig. 6a, 6b and 6c and S4 Figs. 2a,2b and 2c.
In the Guinea savannah, the potential reported cases of uncomplicated malaria averted by 2030 is predicted to be 25.9% at a baseline protective efficacy of IRS of 30% and 30.5% at a protective efficacy of 60% Fig. 6a,S4 Fig. 2a.
With regards to all cases of malaria reported by program target dates, the predicted rates of incidence in the Guinea savannah could be reduced to 150 (95% p.CI [99, 222])/1000 and 112 (95% p.CI [65, 174])/1000 population for an IRS coverage of 80% and 90% respectively for a protective efficacy of 30% and 60% in 2020. By 2030, rates could be as low as 113 (95% p.CI [48, 183])/1000 and 18 (95% p.CI [2, 44])/1000 population respectively, S4 Table 1.
The corresponding potential uncomplicated cases of malaria averted in the Transitional forest zone as shown on Fig. 6b, S4 Fig. 2a could be 49.3% and 54.4% by 2030 for a coverage level of 80% and PE of 30% and 60% respectively.
These declines could translate into a reduction in the rates of incidence of all cases of malaria reported to 163 (95% p.CI [132, 197])/1000 and 129 (95% p.CI [101, 158])/1000 population by 2020 and 50 (95% p.CI [19, 79])/1000 and 2 (95% p.CI [1, 2])/1000 by 2030 respectively for a 30% and 60% levels of IRS PE, S4 Table 2.
Similar predictions are also observed for the Coastal savannah where the possible proportion of cases averted could be 58.9% and 62.9% for a 30% and 60% IRS PE by 2030, Fig. 6c,S4 Fig. 2a and Figs. 2b and 2c for severe and malaria in pregnancy cases reported.
Possible incidence rates for all cases of malaria (uncomplicated and severe) of 150 (95% p.CI [99, 222])/1000 and 150 (95% p.CI [99, 222])/1000 population could be attained by 2020 and 150 (95% p.CI [99, 222])/1000 and 150 (95% p.CI [99, 222])/1000 by 2030 respectively for IRS PE of 30% and 60%, S5 Table 3.
IRS coverage of 90% and PE of 30% and 60%, LLIN coverage and usage at baseline levels (66% and 56% in the Guinea savannah, 51% and 45% in the Transitional forest and 50% and 35% in the Coastal savannah respectively)
Relatively higher cases of uncomplicated, severe malaria and malaria in pregnancy could be potentially averted with a higher IRS coverage of 90% at the similar levels of PE at 30% and 60% across all the zones, Figs. 7a-7c, S4 Figs. 1a-1c, and 2a-2c and 3a-3 c.
In the Guinea savannah, a possibly 72.0% and 79.0% of uncomplicated cases averted could be attained by 2030. Correspondingly, similarly proportions of severe malaria cases and of malaria in pregnancy could be averted by 2030 with an 90% IRS coverage and PE of 30% and 60% respectively, Fig. 7a, S 4 Fig. 1a,2a, 3a.
The impact of these declines in cases of malaria on incidence of all malaria cases could be a decline to 146 (95% p.CI[95, 218])/1000 and 105 (95% p.CI[59, 164])/1000 population by 2030 and 102 (95% p.CI[36, 169])/1000 and 6 (95% p.CI[1, 15])/1000 population by 2030 for a 30% and 60% PE and coverage of 90% IRS, S5 Table 1.
Likewise, in the Transitional forest, potentially 75.7%, of uncomplicated (similarly for severe malaria and malaria in pregnancy cases) could be averted with an IRS coverage of 90% and PE of 30% respectively. For an IRS PE of 60%, the reported cases that could be averted is 78.5of uncomplicated cases may be averted by 2030, Fig. 7b, S4 Figs. 2a-2c.
Consequently, the rates of incidence of all cases of malaria may be lowered by to 159 (95% p.CI[128, 192]) and 121 (95% p.CI[94, 149]) for an IRS PE of 30% and 60% by 2020 and 35 (95% p.CI[12, 59]) and 1 (95% p.CI[1, 1]) for an IRS PE of 30% and 60% by 2030, S5 Table 2.
The impact of IRS only, in averting uncomplicated cases, as shown in Fig. 7c S2 & S3 Fig. 4a, 4b and 4c, S4 Figs. 2b and 2c, could be 78.5% versus 80.9% for a 90% IRS coverage with a 30% and 60% levels of PE respectively for uncomplicated malaria by 2030.
The incidence rates for all cases of malaria following the attainment of these intervention targets could potentially be 75 (95% p.CI[59, 89])/1000 and 53 (95% p.CI[40, 65])/1000 population for 30% and 60% IRS PE by 2020 and 8 (95% p.CI[3, 20])/1000 and 0 (95% p.CI[0, 0])/1000 population by 2030, S5 Table 3.
Deployment of LLINs and IRS
LLIN coverage at 80% and IRS coverage at 80% or 90% with LLIN usage and IRS PE at baseline settings (56% and 30% in the Guinea savannah,45% and 30% in the Transitional forest and 35% and 30% in the Coastal savannah respectively)
Achieving 80% LLINs and IRS coverage while maintaining the LLIN usage and IRS PE at baseline respectively in the population potentially results a 30.8%of reported uncomplicated malaria cases averted in the Guinea savannah, Fig. 8a, and S4 Figs. 3a 3b and 3c.
The proportions of malaria cases averted for implementing an 80% LLIN and IRS coverage at baseline LLIN usage and IRS PE result in terms of incidence rates are 144 (95% p.CI[93, 214])/1000 and 103 (95% p.CI[37, 170])/1000 population for all cases of malaria in the Guinea savannah by 2020 and 2030 respectively, S5 Table 1.
Corresponding proportions of cases averted potentially with IRS coverage increased to 90% as shown on Fig. 8a, S4 Figs. 3a, 3b and 3c are 34.4%, for reported uncomplicated. The accompanying incidence rates for all cases of malaria predicted in 2020 and 2030 are 140 (95% p.CI[90, 210])/1000 and 91 (95% p.CI[27, 156])/1000 population respectively.
In the Transitional forest zone, 58.0% of uncomplicated cases are predicted to be averted and similarly for cases of severe malaria and malaria in, Fig. 8b, S4 Fig. 3a,3b and 3c.
The resulting incidence rates, as shown in S5 Table 2 are 150 (95% p.CI[120, 183])/1000 and a 29 (95% p.CI[9, 51])/1000 population for the Transitional forest respectively for 2020 and 2030. The associated potential proportions of uncomplicated malaria, severe malaria and malaria in pregnancy cases averted under similar intervention scenario as before but with an elevated coverage of IRS to 90% is 60.6%, Fig. 8b, S4 Figs. 3a,3b,and 3c. Corresponding incidence rates for all cases of malaria under this scenario are predicted to be 146 (95% p.CI[116, 178])/1000 and 20 (95% p.CI[6, 36])/1000 population respectively, S5 Table 2.
Under the 80% coverage for both LLIN and IRS and LLIN usage and IRS PE at baseline, the associated potential proportions of uncomplicated, severe and malaria in pregnancy cases averted in the Coastal savannah are predicted to be 64.7respectively, Fig. 8c, S4 Figs. 3a,3b,and 3c.
Predictions of the incidence rates per 1000 for the Coastal savannah under this intervention scenario are predicted to be 72 (95% p.CI[56, 85])/1000 and a 7 (95% p.CI[3, 18])/1000 population for 2020 and 2030 respectively, S5 Table 3.
When only the coverage levels of IRS is increased to 90% while the other intervention scenarios are maintained, the incidence rates per 1000 population are predicted to be 69 (95% p.CI[54, 82]) and 5 (95% p.CI[2, 12]) in the Coastal savannah by 2020 and 2030 respectively, S5 Tables 3. Shown on S4 Figs. 3a, 3b and 3c are the respective proportions of potential cases (66.3%) of uncomplicated malaria, severe malaria and malaria in pregnancy predicted to be averted.
LLIN and IRS coverage at 90% and 80% versus 90% and 90% respectively with LLIN usage and IRS PE baseline (56% and 30% in the Guinea savannah,45% and 30% in the Transitional forest and 35% and 30% in the Coastal savannah respectively)
Given that, baseline usage of LLIN and PE of IRS remain in force as in the previous scenario except increasing the coverage levels of LLINs to 90% and maintaining IRS coverage at 80%, the incidence rates per 1000 population are predicted in the Guinea savannah zone to be 139 (95% p.CI[89, 209]) and 94 (95% p.CI[29, 161]) respectively by 2020 and 2030, Fig. 9a and S5 Table 1,
versus 136 (95% p.CI[86, 204])/1000 population by 2020 and 83 (95% p.CI[20, 146]) by 2030 which is less compared to the previous scenario,S5 Table 1 and Fig. 9a. For a scenario with an increased LLIN coverage at 90% and IRS coverage at 90% .The accompanying proportions of the various of cases of predicted reported malaria are shown on S4 Figs. 3a,3b and 3c.
The observed rates for the Transitional forest are 146 (95% p.CI[116, 178])/1000 and 142 (95% p.CI[113, 173])/1000 population versus 24 (95% p.CI[7, 42])/1000 and 16 (95% p.CI[5, 29])/1000 population respectively by 2020 and 2030, S5 Tables 2, Fig. 9b.
Related predictions of proportions of uncomplicated malaria, severe malaria and malaria in pregnancy are shown on S4 Figs. 3a, 3b and 3c respectively.
Testing a 90% LLIN and 80% IRS coverage versus 90% LLIN and 90% IRS coverage under baseline prevailing levels of LLIN usage and IRS PE, predicted 70 (95% p.CI[54, 83])/1000 and 67 (95% p.CI[52, 80])/1000 population versus 6 (95% p.CI[2, 15])/1000 and 4 (95% p.CI[2, 10])/1000 population respectively by 2020 and 2030, S5 Tables 2, Fig. 9c. Corresponding cases potentially averted in proportions are shown on S4 Figs. 3a, 3b and 3c, respectively for uncomplicated, severe malaria and malaria in pregnancy.
LLIN and IRS coverage at 80% and 80% versus 80% and 90% respectively maintaining LLIN usage at 60% and IRS PE baseline (30% in the Guinea savannah, 30% in the Transitional forest and 30% in the Coastal savannah respectively)
A scenario with an elevated level of LLIN usage in the presence of IRS at baseline PE and LLIN and IRS coverage levels of 80% versus 80% or 80% versus 90% predicts 33.0% versus 37.7% uncomplicated malaria respectively in the Guinea savannah in 2030, S4 Figs. 3a, 3b and 3c.
Equivalently, the incidence rates for all malaria cases predicted are 140 (95% p.CI([89, 210]) versus 137 (95% p.CI([86, 206]) for 2020 and 98 (95% p.CI([33, 165]) versus 86 (95% p.CI([23, 151]) by 2030 respectively, S5 Table 1 and Fig. 10a.Under the same scenario of interventions, the predictions in the Transitional forest zone by 2020 are 65.6% versus 68.3% for uncomplicated malaria respectively by 2020, S4 Figs. 3a,3b and 3c.
The rates of incidence for all cases are however respectively 133 (95% p.CI ([103, 163])/1000 versus 129 (95% p.CI ([100, 159])/1000 population by 2020 and 140 (95% p.CI([89, 210]) /1000 versus 140 (95% p.CI([89, 210])/1000 population by 2030, S5 Table 2, Fig. 10b.
In the Coastal savannah, uncomplicated malaria, severe malaria and malaria in pregnancy cases by 2020 under the same scenario of interventions leads to 74.6% versus 76.1 respectively potentially averted, S4 Fig. 3a, 3b and 3c.Correspondingly, 55 (95% p.CI ([41, 68])/1000 versus 53 (95% p.CI ([39, 66])/1000 population by 2020 and 2 (95% p.CI ([1, 6])/1000 versus 2 (95% p.CI ([1, 4])/1000 population by 2030 are the predicted rates of incidence respectively for the two scenarios of LLINs and IRS being tested,S5 Table 3, Fig. 10c.