{"paper_id":"80857ffd-2488-40b1-8251-8c342d00d6e1","body_text":"1\nImpact of the COVID-19 pandemic on the malaria burden in northern Ghana: Analysis 1 \nof routine surveillance data 2 \nAnna-Katharina Heuschen 1*, Alhassan Abdul-Mumin 2, Martin Nyaaba Adokiya 3, Guangyu 3 \nLu4, Albrecht Jahn1, Oliver Razum5, Volker Winkler1, Olaf Müller1 4 \n 5 \n*Corresponding author 6 \n 7 \n1 Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, 8 \nGermany 9 \n2 University for Development Studies, School of Medicine, Department of Pediatrics 10 \nand Child Health, Tamale, Ghana 11 \n3 University for Development Studies, School of Public Health, Department of 12 \nEpidemiology, Biostatistics and Disease Control, Tamale, Ghana 13 \n4 School of Public Health, Medical School, Yangzhou University, China 14 \n5 Department of Epidemiology and International Public Health, School of Public 15 \nHealth, Bielefeld University, Germany  16 \n 17 \nAbstract 18 \nIntroduction: The COVID-19 pandemic and its collateral damage severely impact 19 \nhealth systems globally and risk to worsen the malaria situation in endemic countries. Malaria 20 \nis a leading cause of morbidity and mortality in Ghana. This study aims to analyze routine 21 \nsurveillance data to assess possible effects on the malaria burden in the first year of the 22 \nCOVID-19 pandemic in the Northern Region of Ghana.  23 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n 2\nMethods: Monthly routine data from the District Health Information Management 24 \nSystem II (DHIMS2) of the Northern Region of Ghana were analyzed. Overall outpatient 25 \ndepartment visits and malaria incidence rates from the years 2015 to 2019 were compared to 26 \nthe corresponding data of the year 2020.  27 \nResults: Compared to the corresponding periods of the years 2015 to 2019, overall 28 \nvisits and malaria incidence in pediatric and adult outpatient departments in northern Ghana 29 \ndecreased in March and April 2020, when major movement and social restrictions were 30 \nimplemented in response to the pandemic. Incidence slightly rebounded afterwards in 2020 31 \nbut stayed below the average of the previous years. Data from inpatient departments showed 32 \na similar but more pronounced trend when compared to outpatient departments. In pregnant 33 \nwomen, however, malaria incidence in outpatient departments increased after the first 34 \nCOVID-19 wave.  35 \nDiscussion: The findings from this study show that the COVID-19 pandemic affects 36 \nthe malaria burden in health facilities of Ghana, with declines in in- and outpatient rates. 37 \nPregnant women may experience reduced access to intermittent preventive malaria treatment 38 \nand insecticide treated nets, resulting in subsequent higher malaria morbidity. Further data 39 \nfrom other African countries, particularly on community-based studies, are needed to fully 40 \ndetermine the impact of the pandemic on the malaria situation. 41 \n 42 \nKeywords 43 \nCOVID-19, pandemic, malaria, sub-Saharan Africa, Ghana, Northern Region, health 44 \ninformation system, surveillance, morbidity, routine data  45 \n 46 \nIntroduction 47 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 3\nMalaria remains one of the leading causes of morbidity and mortality in sub-Saharan 48 \nAfrica (SSA). It is responsible for nearly one quarter of all under five childhood deaths in this 49 \nregion (1, 2).  50 \nThe global spread of the coronavirus disease 2019 (COVID-19) was declared a Public 51 \nHealth Emergency of International Concern, which is the highest level of alarm, at the end of 52 \nJanuary 2020 (3). Many African governments responded rapidly to this threat by 53 \nimplementing control measures even before first cases were detected in their countries, 54 \ncomprising border closures, movement restrictions, social distancing and school closures (4). 55 \nBy November 2021, there were nearly 6.2 million COVID-19 cases reported from the WHO 56 \nAfrican Region, with about 152,000 deaths, mostly from the southern and northern rims of 57 \nthe continent (5). In the global context, SSA accounts for only about 2.5% and 3% of the 58 \noverall reported COVID-19 morbidity and mortality, respectively, while it is home to 17% of 59 \nthe global population (6-8). This may be explained by factors such as a younger population, 60 \nhotter climate, interferences with other infectious diseases, and especially lack of diagnostics 61 \nand underreporting (9, 10). Ghana is among the countries with the highest reported COVID-62 \n19 cases (130,920) and deaths (1,209) in western and central SSA, as of November 2021 (8). 63 \nCOVID-19 vaccinations started in February 2021 but coverage in Ghana is still low with only 64 \n2.7% of the population fully vaccinated by November 2021 (11).  65 \nThe socio-economic disruptions associated with the disease and the preventive 66 \nmeasures present huge challenges for health systems and whole societies, especially in low- 67 \nand middle income countries (12). In the highly malaria-endemic African countries, the 68 \nprogress made in malaria control during the last two decades is feared to be reversed by the 69 \nside effects of the COVID-19 pandemic (13, 14).  70 \nThis study aims to compare the malaria burden in the Northern Region of Ghana in 71 \nthe first year of the pandemic to previous years to assess whether a reversal indeed occurred. 72 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 4\n 73 \nMethods 74 \nStudy area 75 \nGhana, with its population of about 31 million, lies in western SSA and has a 76 \nrelatively well functioning health care system (15, 16). Ghana is divided into 16 77 \nadministrative regions. The Northern Region, with its capital city Tamale, had a population of 78 \n1.9 million in 2020. The socio-economic situation of the Northern Region is below the 79 \nnational average of the country and the region has the highest rate of mortality under the age 80 \nof five years (17). The rainy season in northern Ghana, which is usually associated with an 81 \nincrease in the malaria incidence, lasts from May to October (18).  82 \nMalaria is highly endemic in Ghana; the country accounts for 2% of the global 83 \nmalaria morbidity and 3% of the malaria mortality (19, 20). In 2020, malaria was the cause of 84 \n34% of all outpatient attendances (21). Treatment expenditures for common diseases like 85 \nmalaria are covered by a health insurance (22).  86 \nThe first two confirmed COVID-19 cases in Ghana were seen on March 12, 2020; two 87 \ndays later, all public gatherings were banned. Travel restrictions and border closures were 88 \nimplemented on March 22, 2020 and the country’s major cities were placed under partial 89 \nlockdown soon after. Schools were partially reopened on June 21, 2020 and borders were 90 \nreopened to international airlines on September 21, 2020 (23). In Ghana, effects of the 91 \nCOVID-19 pandemic on malaria control interventions concerned the country’s stock of 92 \nartemisinin-based combination therapies (ACT), the functioning of its insecticide-treated 93 \nmosquito net (ITN) routine distribution, and the overall access to primary health care services 94 \nand facilities (24). 95 \n 96 \nStudy design and data 97 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 5\nThis retrospective observational study uses monthly malaria morbidity data on the 98 \noverall number of outpatients (interpreted as less severe cases) and inpatients (more severe 99 \ncases). Additionally, all outpatient visits (including non-malaria related visits) are analyzed. 100 \nCases were extracted from the district health information management system II  (DHIMS2) 101 \non demographic and health parameters of northern Ghana from January 1, 2015, to December 102 \n31, 2020. This system was implemented in 2007 with an update in 2012 and has improved the 103 \ndata quality and completeness since (25).  104 \nMalaria diagnosis was based either on the results of rapid diagnostic tests or microscopy.  105 \nMid-year population estimates of the Northern Region of Ghana were also provided through 106 \nthe DHIMS2. 107 \n 108 \nAnalysis 109 \nThe data have been processed with Microsoft Excel Version 16.52 and analyzed with 110 \nStata IC Version 16 (Statacorp, College Station, TX, USA). We have calculated and plotted 111 \nmonthly incidence rates of all outpatient visits and confirmed malaria cases for the year 2020 112 \nand as a comparison for the years 2015 to 2019 separately and combined using population 113 \nfigures of the Northern Region of Ghana. Additionally, we calculated incidence rate ratios 114 \nwith 95% confidence intervals (95% CI) comparing quarterly incidence rates of 2020 versus 115 \nthe combined rates of 2015 to 2019. The data allowed analyzing children under five years and 116 \npregnant women separately using the fraction of the under-five population (14% of the 117 \npopulation) and the fraction of women between 15 and 45 years (23% of the population) as 118 \nestimates of the respective population denominators (26). 119 \n 120 \nResults 121 \n Number Percentage (%) \noutpatient department visits \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 6\nAll 5,804,910 100 \nMalaria confirmed 2,278,296 39 \nMalaria confirmed among \nchildren <5 years \n454,779 20 \nMalaria confirmed among \npregnant women \n46,693 2 \nhospital-admitted patients \nMalaria confirmed 295,465 100 \nMalaria confirmed among \nchildren <5 years \n165,313 56 \nmean mid-year population \nTotal population 1,842,701 100 \nChildren <5 years* 257,978 14 \nWomen aged 15 to 45* 423,821 23 \nTable 1: Description of the dataset 122 \n 123 \nTable 1 presents a brief description of the dataset. Altogether 5.8 million outpatient 124 \ndepartment visits were reported between 2015 and 2020; 39% of those included a malaria 125 \ndiagnosis. Of all confirmed malaria cases, 20% were children under the age of five years and 126 \n2% were pregnant women. 295,465 patients were hospitalized with diagnosed malaria, 56% 127 \nof those were children under the age of five years. The mean population of the years from 128 \n2015 to 2020 was 1,842,701 with 14% of children under the age of five years and 23% of 129 \nwomen between the age of 15 and 45 considered as of possible childbearing age.  130 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 7\n 131 \nFigure 1: Reported monthly incidence rates per 100,000 of the Northern Region, Ghana for 132 \nthe years 2015 to 2020 133 \n 134 \nFigure 1 presents the incidence rates of the different outcomes reported in the 135 \nNorthern Region of Ghana for the years between 2015 and 2020 separately as well as a 136 \ncombined rate for the period 2015 to 2019. All visits of the outpatient department (OPD) (see 137 \nFigure 1a), including also non-malaria patients, have experienced a major decline in 138 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 8\nMarch/April 2020, the months where COVID-19 control measures were implemented in the 139 \ncountry, and stayed low during the following months. After a further decrease in September 140 \n2020, the numbers increased again in October 2020 to the levels observed in previous years. 141 \nThis trend is similar but not as pronounced in the general malaria OPD visits (Figure 1b). In 142 \nchildren under the age of five years, the decline in accessing OPD malaria health care is 143 \nstronger, especially from June to September 2020 (Figure 1 c). In pregnant women, however, 144 \na different trend with an earlier increase, starting in June and exceeding previous year’s 145 \nlevels, can be observed (Figure 1d). The 2020 numbers of the hospitally admitted malaria 146 \npatients stayed below the previous standards from March to October 2020 (Figure 1e); and in 147 \naccordance with the OPD figures, this trend is more pronounced in the children under five 148 \nyears population (Figure 1f).  149 \n 150 \nIncidence rate ratios (IRR) depicting quarterly measures comparing the rates of 2020 151 \nto the combined rate of the years 2015 to 2019 are presented in table 2. General OPD visits 152 \nwere reduced in the 2 nd and 3 rd quarters of 2020 compared to the previous years (IRR 3 rd 153 \nquarter 0.736) with a return to previous standards at the end of the year. The same applies to 154 \nthe overall malaria cases (IRR 0.742 in the 3 rd quarter) but with increases in the 4 th quarter 155 \n(IRR 1.265). Ambulatory malaria cases in children under five experienced stronger 156 \nreductions compared to previous years with an IRR 0.566 in the 3 rd quarter of 2020. These 157 \nevolutions are not mirrored by the population of pregnant women with malaria infections, 158 \nwhere no major reductions were observed during the first quarters of 2020 compared to 159 \nprevious years but with an earlier increase (IRR 1.481 in the 4 th quarter). The situation is 160 \nslightly different in malaria infected patients admitted to the hospital. The reductions in the 161 \n2nd and 3 rd quarters of 2020 are more pronounced (IRR 0.548 for all ages in the 2 nd quarter) 162 \nand the numbers do not fully recover at the end of the year. Again, as for the outpatient 163 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 9\npopulation, this trend is more pronounced in children under five years of age (IRR 0.465 in 164 \nthe 2nd quarter). 165 \n 166 \nOutcome IRR (95% CI)  \n1st Quarter \nIRR (95% CI)  \n2nd Quarter \nIRR (95% CI)  \n3rd Quarter \nIRR (95% CI)  \n4th Quarter \noutpatient department visits \nAll  0.930 \n(0.925-0.934) \n0.800 \n(0.796-0.804) \n0.736 \n(0.732-0.739) \n1.026 \n(1.022-1.030) \nMalaria 1.035 \n(1.026-1.044) \n0.899 \n(0.892-0.907) \n0.742 \n(0.737-0.746) \n1.265 \n(1.258-1.272) \nMalaria children <5 years 0.956 \n(0.937-0.974) \n0.806 \n(0.790-0.823) \n0.566 \n(0.557-0.575) \n1.190 \n(1.176-1.206) \nMalaria pregnant women 0.865 \n(0.815-0.918) \n0.957 \n(0.905-1.011) \n1.136 \n(1.091-1.182) \n1.481 \n(1.424-1.540) \nhospital-admitted patients \nMalaria 0.799 \n(0.780-0.817) \n0.548 \n(0.531-0.565) \n0.574 \n(0.563-0.586) \n0.946 \n(0.930-0.962) \nMalaria children <5 years 0.749 \n(0.726-0.773) \n0.465 \n(0.445-0.486) \n0.435 \n(0.422-0.448) \n0.820 \n(0.800-0.839) \nTable 2: Quarterly incidence rate ratios (IRR) with 95% confidence intervals (95% CI) 167 \ncomparing the incidence rates of 2020 with the combined incidence rates of the years 2015 to 168 \n2019 169 \n 170 \nDiscussion 171 \nSince the beginning of the COVID-19 pandemic, several modelling studies have predicted 172 \nnegative collateral effects on the malaria burden in SSA, considering especially disrupted 173 \nITN campaigns and a limited access to antimalarial drugs. The study team of Weiss et al. 174 \ncreated nine scenarios for different reductions of ITN coverage and access to antimalarial 175 \nmedication as well as regarding effects on malaria morbidity and mortality. As no ITN mass 176 \ncampaigns were scheduled for 2020 in Ghana, the worst-case scenario would have been a 177 \ndecline in access to antimalarials by 75% resulting in an increase of malaria morbidity and 178 \nmortality by 12.6% and 54.6%, respectively (13). Overall, the predicted public health 179 \nrelevant effects of the COVID-19 pandemic on malaria include shared clinical disease 180 \nmanifestations leading to diagnostical challenges, disruptions of the availability of curative 181 \nand preventive malaria commodities, significant effects on malaria programs, and in 182 \nparticular reduced access to malaria health services and health facilities in general (27).  183 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 10\n In this study, we observed a slight but significant decline in malaria incidence during 184 \nthe 2nd and 3rd quarter of 2020 (April to September), and only a rebound to the average levels 185 \nof previous years at the end of 2020. This pattern was visible in both, outpatient and inpatient 186 \nsettings, but more pronounced in the hospitalized population. The same applies to children 187 \nand adults, where the reductions were also observed in both groups, but were more marked in 188 \nchildren under five years of age. The marked decline in March/April 2020 can be explained 189 \nby the extensive restrictions of movement and gathering and early stay-at-home advices for 190 \nCOVID-19-like symptoms unless these get severe. Such measures have likely supported the 191 \nhesitancy to visit health facilities during the pandemic, which in turn poses a major risk for 192 \ndeveloping severe malaria (12, 28). The decline observed in March/April 2020 was even 193 \nmore remarkable in inpatients. This does not support our initial hypothesis, that in cases of 194 \nmore severe malaria manifestation, patients were still brought to health facilities and 195 \nhospitalized, despite the pandemic. The findings from this analysis support the hypothesis, 196 \nthat the reported malaria burden in health facilities will shrink due to the effects of the 197 \nCOVID-19 pandemic in highly malaria-endemic countries (Heuschen et al. 2021). They also 198 \nsupport results of the WHO World Malaria Report (12), and they agree with results of similar 199 \nstudies from other SSA countries classified as highly endemic for malaria, such as Sierra 200 \nLeone, Uganda and the Democratic Republic of the Congo (29-32).  201 \nThe distinct decrease of OPD visits in the health facilities of northern Ghana in 202 \nSeptember 2020 may also be explained by unusual heavy floods that started mid-August and 203 \ncould have further complicated the access to health services. Flooded land is a favorable 204 \nhabitat for Anopheles mosquitos, the malaria vector, what could have led to the observed 205 \nincreases of malaria incidence in October 2020. 206 \n Malaria incidence among pregnant women shows a different trend in northern Ghana. 207 \nAfter a decline in reported malaria cases in April 2020, malaria figures have rebounded 208 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 11\nrapidly in this population and reached even higher levels compared to previous years. The 209 \nmost likely explanation of such an opposite trend would be the hesitancy of pregnant women 210 \nto visit health facilities. This is probably due to the fear of getting infected with COVID-19, 211 \ncombined with initial disruptions of the provision of intermittent preventive treatment in 212 \npregnancy (IPTp) to women in antenatal care (ANC) services as well as the disruption of 213 \nroutine distribution of ITNs (33). The disrupted access to and delivery of ANC services is 214 \nlikely to explain the malaria case trend in April. However, without IPTp and ITNs, more 215 \nwomen were at risk for malaria thereafter, which can explain the subsequent rise in malaria 216 \ncases over the following months. Also, many pregnant women probably have sought the 217 \nmissed ANC after the initial movement restrictions were lifted with subsequent malaria 218 \ndiagnosis.  219 \nGhana had already achieved high levels of ITN coverage, and no ITN mass campaign 220 \nwas planned for 2020 (12). However, the routine distribution of ITNs, which is usually done 221 \nin health facilities during ANC sessions and in primary schools, needed to be adapted to the 222 \nCOVID-19 measures, which included school closure from March 2020 until January 2021 223 \n(34, 35). Also the seasonal malaria chemoprevention intervention for children and the annual 224 \nindoor residual spraying of insecticides, which both require physical contact between the 225 \nhealth workers and the community, needed to be modified (36, 37). As another consequence 226 \nof the COVID-19 pandemic, the provision of rapid diagnostic tests for malaria is fragile, 227 \nwhich may have led to under-diagnosis of cases (38). Finally, reports of hesitancy to visit 228 \nhealth facilities due to fear of getting infected with COVID-19 are still common (33, 38). 229 \nLast but not least, the malaria health care workers capacities were limited due to frequent 230 \nreassignments to the control of COVID-19, to stigmatization or absence following 231 \nquarantine, or to the development of COVID-19 disease or even death (13, 35, 39). 232 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 12\nThis study has strengths and limitations. A strength of the study is that the data 233 \nrepresent a whole year of follow-up into the pandemic, which provides a more 234 \ncomprehensive picture of the effects compared to the previous studies with much shorter 235 \nstudy periods. Limitations are that the surveillance system itself may have been affected by 236 \nthe pandemic, with a bias in the reported numbers. Moreover, it is not clear if the quality of 237 \nsurveillance data is fully comparable during the five years observed. Finally, much more 238 \npeople with malaria symptoms may have switched to self-medication during the pandemic, 239 \nwhich may also have an albeit unknown effect on the malaria figures. 240 \n 241 \nIn conclusion, this study shows that the COVID-19 pandemic has been accompanied 242 \nby a reduced malaria incidence in northern Ghana’s health facilities. Further data from other 243 \nAfrican countries and in particular data from community-based studies are needed to fully 244 \njudge the impact of the pandemic on the global malaria situation.  245 \n 246 \nDeclarations 247 \nEthics approval and consent to participate 248 \n No ethical approval and consent to participate was required as only secondary data 249 \nhave been used. 250 \n 251 \nConsent for publication 252 \n No consent for publication was required (only secondary data used). 253 \n 254 \nAvailability of data and material 255 \n The datasets used and/or analyzed in this study are available from the corresponding 256 \nauthor on reasonable request. 257 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted November 29, 2021. ; https://doi.org/10.1101/2021.11.29.21266976doi: medRxiv preprint \n\n 13\n 258 \nCompeting interests 259 \nThe authors declare that they have no competing interests. 260 \n 261 \nFunding 262 \n Anna-Katharina Heuschen acknowledges the support by the Else Kröner-Fresenius-263 \nStiftung within the Heidelberg Graduate School of Global Health. 264 \n 265 \nAuthors' contributions 266 \nAAM and MNA were responsible for the data collection. AH, VW and OR performed 267 \nthe data analysis. AH wrote the first draft under the supervision of OM, AAM and MNA 268 \nsupported the data interpretation. All authors read, reviewed and approved the final 269 \nmanuscript. 270 \n 271 \nAcknowledgements 272 \n We acknowledge financial support by the Else Kröner-Fresenius-Stiftung within the 273 \nHeidelberg Graduate School of Global Health, by Deutsche Forschungsgemeinschaft within 274 \nthe funding programme Open Access Publishing, by the Baden-Württemberg Ministry of 275 \nScience, Research and the Arts and by Ruprecht-Karls-Universität Heidelberg. 276 \n 277 \nBibliography 278 \n1. Gl o bal  B urden of D is ease, Viz  H ub [Int ernet ] . U niversity of Was hingt on. 20 21 [cited 279 \n30.04.2 021]. A v ailable f r om: https : / /vizhub.health data.org/gbd-compar e /.  280 \n2. Müller  O . M al ar ia in A fr ica: chall enge s for  cont rol and elim ination  in t he  21s t  281 \ncentur y :  Pet er Lang F r ankfurt ; 2011.  282 \n3. WHO. Ti m eli n e o f W H O ’s respon se to COV ID -19. 202 1.  283 \n4. WHO. 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